57 Data Classification Jobs in Ghaziabad

Job Description Data Scientist Role: Data Scientist Experience: 3-4 years Location: Gurgaon (Hybrid) Role Overview We are seeking a Data Scientist with 34 years of experience in AI/ML and Deep Learning. The role involves building and deploying models for prediction, anomaly detection, NLP, and industrial analytics (predictive maintenance). You will work with cross-functional teams to design scalable pipelines and deliver data-driven solutions that create measurable business impact.  Key Responsibilities: Develop and deploy AI/ML and Deep Learning models for regression, classification, clustering, anomaly detection, and forecasting. Apply Neural Networks, CNNs, RNNs, LSTMs, Transformers, and Autoencoders for solving business problems. Work on NLP techniques (BERT, GPT-based models, text similarity, embeddings, topic modeling). Build predictive analytics and optimization pipelines for industrial/manufacturing domains (predictive maintenance). Perform exploratory data analysis (EDA), feature engineering, and statistical validation. Required Skills Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, Keras). 3-4 years of hands-on experience in AI/ML model development. Expertise in Deep Learning architectures (CNN, RNN, LSTM, Transformer-based models). Solid background in statistical analysis, hypothesis testing, and probability models. Strong knowledge of SQL/Databases (PostgreSQL, InfluxDB) for data extraction and processing. Candidate can be apply from Delhi/NCR  Regard, Ruchi Maurya Talent Acquisition Team 9971720679

Location - LTIM Pan IndiaExperience - 5+to 12+ yrsGeneric JD-Mandatory Skills - Data Science, Gen AI, Python, RAG and Azure/AWS/GCP, AI/ML, NLP Secondary - (Any) Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model DeploymentJD_ More than 6 years of experience in Data Engineering, Data Science and AI / ML domainExcellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc.Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop)Experience in Cloud native skills.Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an assetAnalytical mind and business acumen and Strong math skills (e.g. statistics, algebra)Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable.Experience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc.Great communication and presentation skills. Should have experience in working in a fast-paced team culture.Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc.Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databasesGood understanding of applied statistics skills, such as distributions, statistical testing, regression, etc.Should be a data-oriented person with analytical mind and business acumen.

As a Technical Architect at CLOUDSUFI, you will be responsible for leading the design and implementation of scalable, high-performance data architectures. Your main focus will be on building a unified and intelligent data ecosystem that enables seamless integration of diverse public datasets into our Knowledge Graph using Google Cloud Platform (GCP). To excel in this role, you will need to have a deep understanding of modern data architectures, cloud-native services, and best practices in data integration, knowledge graph modeling, and automation frameworks. **Key Responsibilities:** - Define and own the end-to-end architecture for data ingestion, transformation, and knowledge graph integration pipelines. - Establish best practices for schema modeling, metadata management, and data lineage across GCP environments. - Provide technical leadership and mentorship to Data Engineers and Automation teams. - Architect large-scale, automated ETL/ELT frameworks leveraging GCP services such as Dataflow, BigQuery, Pub/Sub, Cloud Run, and Cloud Storage. - Design schema mapping and entity resolution frameworks using LLM-based tools for auto-schematization and intelligent data classification. - Define standards for integrating datasets into the Knowledge Graph, including schema.org compliance, MCF/TMCF file generation, and SPARQL endpoints. - Establish data quality, validation, and observability frameworks (statistical validation, anomaly detection, freshness tracking). - Implement governance controls to ensure scalability, performance, and security in data integration workflows. - Partner with the Automation POD to integrate AI/LLM-based accelerators for data profiling, mapping, and validation. - Drive innovation through reusable data frameworks and automation-first architectural principles. - Collaborate closely with cross-functional teams (Engineering, Automation, Managed Services, and Product) to ensure architectural alignment and delivery excellence. - Influence and guide architectural decisions across multiple concurrent projects. **Qualifications and Experience:** - **Education:** Bachelors or Masters in Computer Science, Data Engineering, or a related field. - **Experience:** 8+ years of experience in Data Engineering or Architecture roles, including 3+ years in GCP-based data solutions. - **Technical Expertise:** Must Have: GCP (BigQuery, Dataflow/Apache Beam, Cloud Run, Cloud Storage, Pub/Sub), Python, SQL, Data Modeling, CI/CD (Cloud Build). Good to Have: SPARQL, Schema.org, RDF/JSON-LD, Apigee, Cloud Data Fusion, and knowledge graph concepts. Strong knowledge of data governance, metadata management, and data lineage frameworks. **Preferred Qualifications:** - Experience working with LLM-based or AI-assisted data processing tools (e.g., auto-schematization, semantic mapping). - Familiarity with open data ecosystems and large-scale data integration initiatives. - Exposure to multilingual or multi-domain data integration. - Strong analytical and problem-solving ability. - Excellent communication and stakeholder management skills. - Passion for mentoring teams and driving best practices. This position requires you to have experience working with US/Europe based clients in an onsite/offshore delivery model, strong verbal and written communication skills, technical articulation, listening and presentation skills, effective task prioritization, time management, internal/external stakeholder management skills, quick learning ability, team player mindset, experience of working under stringent deadlines in a Matrix organization structure, and demonstrated Organizational Citizenship Behavior (OCB) in past organizations.,

As an AI Incubator Data Scientist at Barclays, you will embark on a transformative journey to spearhead the evolution of the digital landscape and drive innovation and excellence. Your role will involve harnessing cutting-edge technology to revolutionize digital offerings, ensuring unparalleled customer experiences. You will have the opportunity to shape and lead projects within the AI incubator team, leveraging machine learning techniques and AI to extract valuable insights and create tangible business impact. The position emphasizes a design-led thinking approach with close collaboration with business stakeholders and a fail-fast mindset. You will work with extensive datasets spanning billions of rows, applying state-of-the-art AI techniques to unlock millions in business value. **Key Responsibilities:** - Build relationships with senior stakeholders across the bank to identify opportunities for adding value through Data Science and GenAI. - Develop machine learning models and apply AI to deliver commercial value for the Corporate Bank. - Utilize AWS services for data transformation, feature engineering, AI product development, and deployment. - Communicate complex technical ideas to stakeholders through data visualization. - Collaborate with the ML Ops team in technology to streamline the path to production for successful projects. **Essential Skills and Qualifications:** - Bachelor's or master's degree in data science or equivalent commercial experience. - Experience working with senior stakeholders across the data science lifecycle, from idea inception to delivery in a production environment. - Ability to translate technical work into business terms and communicate value to business stakeholders. - Commercial experience in applying machine learning techniques for generating business value such as clustering, classification, regression, and NLP techniques. - Strong coding skills with a focus on Python and SQL, including a strong understanding of key coding principles like separation of concerns and generalization of code. - Familiarity with AWS data science and AI services, including SageMaker and Bedrock. - Proficiency in data visualization software, ideally Tableau, with exposure to QlikView, PowerBI, or similar tools. - Knowledge of code management methodologies and the ability to implement them on projects. **Desirable Skills/Preferred Qualifications:** - Experience in front-end development frameworks such as Angular/React Flask/Streamlit. - Knowledge of MVC Architecture. - Experience with Agentic AI and working in a big data environment using PySpark. In this role, you will use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves. Your insights will inform strategic decision-making, improve operational efficiency, and drive innovation across the organization. **Accountabilities:** - Identify, collect, and extract data from various sources, including internal and external sources. - Clean, wrangle, and transform data to ensure quality and suitability for analysis. - Develop and maintain efficient data pipelines for automated data acquisition and processing. - Design and conduct statistical and machine learning models to analyze patterns, trends, and relationships in the data. - Develop and implement predictive models to forecast future outcomes and identify risks and opportunities. - Collaborate with business stakeholders to add value from data through Data Science. In conclusion, as an AI Incubator Data Scientist at Barclays, you will play a pivotal role in driving innovation, leveraging cutting-edge technology, and extracting valuable insights to shape the digital landscape and deliver commercial value for the Corporate Bank.,

**Job Description:** As a key member of the team, you will work with the team to analyze and interpret data, develop metrics to measure results, and integrate new methodologies. You will work with large complex data sets, solve difficult non-routine analysis problems, and apply advanced analytical methods as needed. Your responsibilities will include conducting end-to-end analysis that involves data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations. You will be expected to make business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information. **Role and Responsibilities:** - Designing and implementing machine learning, information extraction, probabilistic matching algorithms, and models - Using your passion for programming and deep learning/AI skills using Python, TensorFlow, and deep learning frameworks like Keras, PyTorch to solve real-life problems - Developing AI solutions in the computer vision domain using convolutional neural networks (CNN) and a combination of deep neural networks such as CNN & RNN - Solving object detection, recognition, image classification problems using machine learning and deep learning algorithms & transfer learning methods and techniques - Using innovative & automated approaches for data annotation, labeling, and data augmentation & use active learning - Handling online code assistance, code mentoring, and education-based solutions - Building and prototyping analysis pipelines iteratively to provide insights at scale - Researching and developing analysis, forecasting, and optimization methods to improve the quality of user-facing products such as ads quality, search quality, end-user behavioral modeling, and live experiments **Qualifications Required:** - PhD degree in Statistics, Applied Mathematics, or similar quantitative discipline, or equivalent practical experience - Relevant internship or work experience with data analysis - Experience with statistical software (R, Python, S-Plus, SAS, or similar) and experience with database languages (e.g. SQL) **Preferred Qualifications:** - 1 year of relevant work experience, including experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods - Ability to draw conclusions from data and recommend actions - Demonstrated leadership and self-direction. Demonstrated willingness to both teach others and learn new techniques (Note: The additional details of the company were not provided in the job description.),

In this internship, you are expected to be a good coder who can solve coding problems efficiently. You may be assigned to work on simple and easy programs, but the key aspect is to ensure that you can explain your code clearly for learners and developers worldwide to comprehend. This opportunity will not only enhance your coding skills but also provide valuable research experience. As a Beginner or Intermediate Programmer, you will have the chance to learn and grow through assignments and projects of varying difficulty levels, enabling you to explore your potential and evolve into a better programmer. You will have the flexibility of working from home, which can be a significant advantage for you. There are no strict working hours; as long as you complete the assigned projects on time, you can manage your schedule efficiently and earn your compensation. **Minimum qualifications:** - Degree in Computer Science or related technical field, or equivalent practical experience. - Proficiency in coding using languages like C, C++, Java, JavaScript, or Python. **Preferred qualifications:** - Experience in Algorithms, Artificial Intelligence, Database, Data Mining, Distributed Systems, Machine Learning, Networking, or Systems. - Proficiency in Object Oriented Programming. - Strong foundation in computer science with expertise in data structures, algorithms, and software design. - Coding skills in Python or JavaScript/AJAX, database design and SQL, and/or knowledge of TCP/IP and network programming. - Ability to work independently. **Role and Responsibilities:** - Design and implement machine learning, information extraction, probabilistic matching algorithms, and models. - Utilize programming skills and deep learning/AI expertise using Python, TensorFlow, and frameworks like Keras, PyTorch to solve real-world problems. - Develop AI solutions in the computer vision field using convolutional neural networks (CNN) and a combination of deep neural networks such as CNN & RNN. - Solve object detection, recognition, image classification problems with machine learning and deep learning algorithms & transfer learning methods. - Implement innovative & automated approaches for data annotation, labeling, data augmentation, and active learning. - Provide online code assistance, code mentoring, and education-based solutions. Only candidates who: - are available for a full-time (in-office) internship - can commence the internship from 15th Jun'20 - are willing to commit to a duration of 6 months - possess relevant skills and interests **Perks:** - Certificate, Letter of recommendation - Flexible work hours - Informal dress code - 5 days a week - Free snacks & beverages,

Role Overview: As a Junior Data Scientist in the Data Science team, you will be involved in various business analytics, data engineering, and advanced modeling projects. Your primary focus will be on building clean data pipelines, generating user-level insights, and contributing to complex consumer behavior models. This role offers you the opportunity to work at the intersection of data engineering, analytics, and AI, providing a platform for your professional growth and development. Key Responsibilities: - Support the development of VTION's behavioral data models by cleaning, transforming, and feature engineering - Assist in constructing and automating data pipelines in collaboration with engineering teams - Engage in business analytics projects to translate behavioral data into marketing and user insights - Deliver exploratory analyses, cohort insights, and trend reports to aid strategic decision-making - Contribute to real-time dashboards and visualizations for both internal and client use, utilizing tools like Power BI, Tableau, and Plotly - Work on classification, clustering, and segmentation models using Python libraries such as Scikit-learn, pandas, and NumPy - Collaborate with data scientists, engineers, and product teams to deliver scalable solutions - Participate in sprint reviews, brainstorms, and post-analysis reviews to drive learning and iteration - Continuously explore new tools, methods, and technologies to enhance your professional practice Qualifications Required: - Proficiency in Python, with knowledge of libraries like pandas, NumPy, scikit-learn, and matplotlib - Familiarity with SQL for data querying - Exposure to cloud platforms, with AWS and GCP being preferred - Bonus: Familiarity with Git, Airflow, dbt, or vector databases - Ability to interpret business problems into data questions - Understanding of basic statistics, experiment design, and metrics interpretation - Eagerness to learn in a dynamic, fast-paced environment - Strong communication skills and a collaborative spirit (Note: Additional details about the company were not provided in the job description.) Role Overview: As a Junior Data Scientist in the Data Science team, you will be involved in various business analytics, data engineering, and advanced modeling projects. Your primary focus will be on building clean data pipelines, generating user-level insights, and contributing to complex consumer behavior models. This role offers you the opportunity to work at the intersection of data engineering, analytics, and AI, providing a platform for your professional growth and development. Key Responsibilities: - Support the development of VTION's behavioral data models by cleaning, transforming, and feature engineering - Assist in constructing and automating data pipelines in collaboration with engineering teams - Engage in business analytics projects to translate behavioral data into marketing and user insights - Deliver exploratory analyses, cohort insights, and trend reports to aid strategic decision-making - Contribute to real-time dashboards and visualizations for both internal and client use, utilizing tools like Power BI, Tableau, and Plotly - Work on classification, clustering, and segmentation models using Python libraries such as Scikit-learn, pandas, and NumPy - Collaborate with data scientists, engineers, and product teams to deliver scalable solutions - Participate in sprint reviews, brainstorms, and post-analysis reviews to drive learning and iteration - Continuously explore new tools, methods, and technologies to enhance your professional practice Qualifications Required: - Proficiency in Python, with knowledge of libraries like pandas, NumPy, scikit-learn, and matplotlib - Familiarity with SQL for data querying - Exposure to cloud platforms, with AWS and GCP being preferred - Bonus: Familiarity with Git, Airflow, dbt, or vector databases - Ability to interpret business problems into data questions - Understanding of basic statistics, experiment design, and metrics interpretation - Eagerness to learn in a dynamic, fast-paced environment - Strong communication skills and a collaborative spirit (Note: Additional details about the company were not provided in the job description.)

Role Overview: You will be responsible for leveraging your 3+ years of experience in Data Science, machine learning, or related fields to tackle structured and unstructured data problems. Your expertise in Machine Learning and Statistics will be crucial as you develop, implement, and deploy machine learning models on cloud platforms such as Azure, AWS, and GCP. Your role will involve integrating machine learning models into existing systems, developing MLOps pipelines, monitoring model performance, and providing insights to stakeholders. Key Responsibilities: - Apply practical experience in time series forecasting, clustering, classification techniques, regression, boosting algorithms, optimization techniques, NLP, and recommendation systems - Utilize programming skills in Python/PySpark and SQL to develop and implement machine learning models - Deploy machine learning models on cloud platforms using AWS/Azure Machine Learning, Databricks, or other relevant services - Integrate machine learning models into systems and applications to ensure seamless functionality and data flow - Develop and maintain MLOps pipelines for automated model training, testing, deployment, and monitoring - Monitor and analyze model performance, providing reports and insights to stakeholders - Demonstrate excellent written and verbal communication skills in presenting ideas and findings to stakeholders Qualification Required: - Engineering Graduate from a reputed institute and/or Masters in Statistics, MBA - 3+ years of experience in Data Science - Strong expertise in machine learning with a deep understanding of SQL & Python - Exposure to industry-specific (CPG, Manufacturing) use cases - Strong client-facing skills - Organized and detail-oriented with excellent communication and interpersonal skills About the Company: Polestar Solutions is a data analytics and enterprise planning powerhouse that helps customers derive sophisticated insights from data in a value-oriented manner. With a presence in the United States, UK, and India, Polestar Solutions boasts a world-class team and offers growth and learning opportunities to its employees. The company has been recognized for its expertise and passion in various accolades, including being featured in the Top 50 Companies for Data Scientists and as Financial Times" High-Growth Companies across Asia-Pacific. (Note: The job description did not provide additional details about the company.),

As a Master Data Manager, you will play a crucial role in ensuring the accuracy, consistency, and integrity of all product-related data across our systems. Your responsibilities will include managing master data processes, developing data quality metrics, collaborating with stakeholders, and overseeing product data management within the Master Data Management (MDM) system. Here's a breakdown of your role: **Role Overview:** In this role, you will be responsible for overseeing the creation, maintenance, and updating of product data within the MDM system. You will work closely with various stakeholders to gather information, resolve data discrepancies, and ensure data governance best practices are followed. **Key Responsibilities:** - Oversee product data creation, maintenance, and updating in the MDM system - Ensure data accuracy, consistency, and standardization across all clients - Collaborate with stakeholders to resolve data discrepancies - Implement data governance best practices - Support product lifecycle management activities - Generate reports and analyze product data trends - Provide training and support on product data management processes **Qualifications Required:** - Bachelor's degree in computer science or equivalent experience in data management and analytics - Minimum 8 years of experience in executing master data management activities - Strong understanding of product data structures and classifications - Proficiency in Microsoft Excel and data standardization tools - Experience with ETL tools and Product Information Management (PIM) tools - SQL understanding - Independent decision-making and troubleshooting skills - Expertise in documenting data definitions - Creative thinker with a willingness to learn new processes **Additional Company Details:** You will be working in a dynamic environment that values collaboration and innovation. Your role will provide you with exposure to global work experience and opportunities to contribute to the growth and success of the organization.,

As a Sr. Design Engineer or Design Engineer in our Consultancy / Design Engineering / EPC Organization related to Refinery / Petrochemical Plant, your role will involve the following: - Experience in Chemical / Process Plant instrumentation - Knowledge of International Standards including preparation of Control Strategy, Control Loop Configuration, and Instrument Classification - Proficiency in designing Logic Diagrams, field instruments, and control systems - Engineering instrument sizing calculations and preparing instrument data sheets and specifications - Conducting Technical Bid Evaluations and collaborating with Control system vendors for system configuration - Reviewing and approving vendor prints, executing Factory Acceptance Tests and Site Acceptance Tests for control and safety systems - Providing input on instrument construction drawings and utilizing INtools for instrument Index, data sheets, hook-up drawings, and loop drawings In terms of qualifications, we are looking for candidates with: - Degree in Instrumentation Engineering (BE / B Tech) from a reputed University - 10 to 15 years of experience for Sr. Design Engineer, with at least 5 years in a similar role - 5 to 10 years of experience for Design Engineer, with at least 3 years of working experience in the relevant industry If you are the right candidate for this position, you can expect a remuneration that is best in the industry. To apply, please get in touch with our HR Manager, Sarita Verma, at +91-129-4311626 or via email at sarita@grengineering.co.in.,

Role Overview: In this role, you will be responsible for determining and escalating high-risk triggers, potential risk findings, and the maintenance of accurate and complete documents into our customer databases. You will collaborate with various stakeholders globally to fulfill an entity's KYC requirements as mandated by compliance and regulatory standards. You will have an exciting opportunity to join a collaborative team that delivers exceptional business and risk outcomes to stakeholders through efficient and high-quality client onboarding. Key Responsibilities: - Determine and escalate high-risk triggers and potential risk findings. - Maintain accurate and complete documents in customer databases. - Collaborate with various stakeholders globally to fulfill entity's KYC requirements. - Deliver exceptional business and risk outcomes through efficient and high-quality client onboarding. - Foster innovation and lead change initiatives to enhance processes. Qualifications Required: - 1-5 years of experience or extensive knowledge in KYC onboarding including AML and non-AML regulatory requirements. - Knowledge in regulations such as Dodd Frank, EMIR/MIFID, or HK professional investor classification will be an advantage. - Experience in a financial institution involving research or KYC due diligence work. - Familiarity with fund entity structures will be an advantage. - Highly organized and able to manage multiple tasks. - Strong communication and stakeholder management skills to clearly articulate complex findings. Additional Company Details: At Macquarie, our advantage lies in bringing together diverse people and empowering them to shape all kinds of possibilities. With 55 years of unbroken profitability, we are a global financial services group operating in 34 markets. You will be part of a friendly and supportive team where everyone contributes ideas and drives outcomes. In the Corporate Operations Group at Macquarie, you will work at the heart of the organization to deliver for our people, businesses, and customers. The group comprises a global, collaborative team with deep expertise in various areas including technology, data, digital, market operations, corporate real estate, business resilience, procurement, and global security. Macquarie offers a range of benefits to its employees such as hybrid and flexible working arrangements, paid parental leave, paid volunteer leave, and access to learning and development opportunities. The company is committed to diversity, equity, and inclusion and provides reasonable adjustments to individuals who may need support during the recruitment process and through working arrangements. Role Overview: In this role, you will be responsible for determining and escalating high-risk triggers, potential risk findings, and the maintenance of accurate and complete documents into our customer databases. You will collaborate with various stakeholders globally to fulfill an entity's KYC requirements as mandated by compliance and regulatory standards. You will have an exciting opportunity to join a collaborative team that delivers exceptional business and risk outcomes to stakeholders through efficient and high-quality client onboarding. Key Responsibilities: - Determine and escalate high-risk triggers and potential risk findings. - Maintain accurate and complete documents in customer databases. - Collaborate with various stakeholders globally to fulfill entity's KYC requirements. - Deliver exceptional business and risk outcomes through efficient and high-quality client onboarding. - Foster innovation and lead change initiatives to enhance processes. Qualifications Required: - 1-5 years of experience or extensive knowledge in KYC onboarding including AML and non-AML regulatory requirements. - Knowledge in regulations such as Dodd Frank, EMIR/MIFID, or HK professional investor classification will be an advantage. - Experience in a financial institution involving research or KYC due diligence work. - Familiarity with fund entity structures will be an advantage. - Highly organized and able to manage multiple tasks. - Strong communication and stakeholder management skills to clearly articulate complex findings. Additional Company Details: At Macquarie, our advantage lies in bringing together diverse people and empowering them to shape all kinds of possibilities. With 55 years of unbroken profitability, we are a global financial services group operating in 34 markets. You will be part of a friendly and supportive team where everyone contributes ideas and drives outcomes. In the Corporate Operations Group at Macquarie, you will work at the heart of the organization to deliver for our people, businesses, and customers. The group comprises a global, collaborative team with deep expertise in various areas including technology, data, digital, market operations, corporate real estate, business resilience, procurement, and global security. Macquarie offers a range of benefits to its e

Role Overview: As a US HR Compliance Specialist supporting US operations from India, your role is crucial in ensuring compliance with US Labor laws, federal and state regulations, and internal company policies. You will collaborate closely with HR Managers on various HR compliance matters. Key Responsibilities: - Monitor and ensure compliance with US federal and state employment laws such as FMLA, ADA, EEOC, FLSA, OSHA, ADEA, etc. - Handle administrative tasks related to HR functions, including maintenance of personnel and medical records. - Maintain accurate employee records in compliance with data privacy regulations like GDPR, CCPA. - Coordinate with US HR and Legal teams on employee relations investigations and compliance matters. - Assist in developing and delivering training on compliance topics including anti-harassment, ethics, and diversity & inclusion. - Track key compliance metrics and prepare regular reports for stakeholders. - Stay updated with changes in US labor laws, court rulings, and agency guidelines affecting employment practices. - Support the administration and monitoring of FMLA, ADA, Emergency Paid Sick Leave, Workers Compensation, and other leave of absence programs. - Review background reports for compliance and process FCRA notices as required. Qualifications: - Bachelor's degree in Human Resources or a related field. - 3 years of experience in HR compliance, preferably supporting US-based HR operations. - Strong understanding of US labor laws and employment classifications (W2, 1099, C2C). - Familiarity with EEO, ADA, FMLA, FCRA, FLSA, Title VII, and other relevant federal and state laws. - Excellent verbal and written communication skills. - High attention to detail and ability to work independently in a remote environment. Please note: Preferred industry experience in US staffing.,

Role Overview: As a Data Analyst, you will provide expertise on data analysis techniques using software tools and streamline business processes under supervision. Your role will involve designing and managing the reporting environment, providing technical expertise on data storage structures, data mining, and data cleansing, as well as supporting the data warehouse in identifying and revising reporting requirements. You will also support initiatives for data integrity and normalization, troubleshoot the reporting database environment, and recommend new ways to streamline business processes. Additionally, you will illustrate data graphically, translate complex findings into written text, and help clients make better decisions by generating reports from single or multiple systems. Training end users on new reports and dashboards will also be part of your responsibilities. Key Responsibilities: - Design and manage the reporting environment including data sources security and metadata - Provide technical expertise on data storage structures, data mining, and data cleansing - Support the data warehouse in identifying and revising reporting requirements - Troubleshoot the reporting database environment and associated reports - Identify and recommend new ways to streamline business processes - Generate reports from single or multiple systems - Illustrate data graphically and translate complex findings into written text - Help clients make better decisions by locating results and soliciting feedback - Train end users on new reports and dashboards Qualifications Required: - 5-10 years of experience in data science/AI-ML/Generative AI development - Hands-on experience in developing complex AI/ML solutions - Strong knowledge of Machine Learning, Deep Learning, Generative AI/LLMs, and various use cases - Ability to apply methods such as predictive analytics, time series analysis, hypothesis testing, classification, clustering, and regression analysis - Proficiency in a core programming language such as Advanced Python, JavaScript's/React/Angular, Scala, Spark - Experience with databases like SQL server, Postgres, ClickHouse, Presto - In-depth understanding of Cloud Platforms such as AWS, GCP, Azure, and ML platforms like SageMaker - Familiarity with Visualization Tools like Tableau, PowerBI - Masters or Bachelors degree in Data Science, Computer Science, or a relevant field - Strong communication skills and ability to drive results through collaboration Additional Details: You should also have knowledge of database languages such as SQL, programming languages such as R or Python, analytical tools and languages such as SAS & Mahout, proficiency in MATLAB, data visualization software such as Tableau or Qlik, proficiency in mathematics and calculations, efficiency with spreadsheet tools such as Microsoft Excel or Google Sheets, DBMS, operating systems and software platforms, and knowledge regarding customer domains and subdomains where problems are solved. Additionally, you should have a strategic mindset with excellent analytical and problem-solving skills and be able to interact with business decision-makers and other AI/ML experts/coders effectively.,

As an Assistant Director - AI/GenAI at EY, you will be responsible for developing and delivering industry-specific solutions using Artificial Intelligence, Machine Learning, deep learning, and LLM models for Generative AI, text analytics, and Python programming. Your role will involve leading the development and implementation of Generative AI applications, working with advanced models like GPT-3.5, GPT 4, Llama, BERT, and optimizing solutions leveraging Vector databases for efficient storage and retrieval of contextual data for LLMs. You will also work on identifying opportunities for analytics applications, managing projects, and ensuring smooth service delivery. **Key Responsibilities:** - Develop, review, and implement solutions applying AI, Machine Learning, and Deep Learning - Lead the development and implementation of Generative AI applications - Work with advanced models for natural language processing and creative content generation - Design and optimize solutions leveraging Vector databases - Understand business sectors and identify opportunities for analytics application - Manage projects and ensure smooth service delivery - Communicate with cross-functional teams - Go-to-market/stakeholder management **Qualifications Required:** - Experience guiding teams on AI/Data Science projects - Familiarity with implementing solutions in Azure Cloud Framework - Excellent presentation skills - 12-16 years of relevant work experience in developing and implementing AI, Machine Learning Models - Experience with statistical techniques, deep learning, and machine learning algorithms - Proficiency in Python programming - Familiarity with software development life cycle (SDLC) - Willingness to mentor team members As an ideal candidate, you should have the ability to think strategically, build rapport within the firm, and travel extensively. EY offers opportunities to work with a global team of professionals in a dynamic and inclusive culture, providing continuous learning and transformative leadership. Join EY and be a part of building a better working world through innovation and collaboration across industries and geographies.,

You will be responsible for building deep learning models using TensorFlow/PyTorch and collaborating with the team to ensure proper testing and deployment. Your role will require a good understanding of Deep Learning Algorithms in both NLP (LSTMs, RNNs, etc.) and Computer Vision (CNNs, etc.) domains using TensorFlow, Keras, and PyTorch to solve real-life problems. You will also be involved in creating and updating documentation for your work and implementing deep learning algorithms such as LSTM, RNNs, DNNs, and BI-LSTMs from scratch. Additionally, you will work on Computer Vision and Image processing tasks, including TRANSFER LEARNING - GANs. Key Responsibilities: - Research machine learning/data science topics for writing articles for company websites - Assist with hands-on coding on Jupyter Notebook for providing code snippets in articles - Work on short projects & assignments, deployment techniques, and design and implement machine learning algorithms - Develop AI solutions in the computer vision domain using CNN and a combination of deep neural networks - Solve object detection, recognition, image classification problems using machine learning and deep learning algorithms, transfer learning methods, and techniques - Use innovative & automated approaches for data annotation, labeling, data augmentation, and active learning - Provide online code assistance, code mentoring, and education-based solutions Qualifications Required: - Master or PhD degree in Statistics, Applied Mathematics, or similar quantitative discipline, or equivalent practical experience - Relevant internship or work experience with data analysis - Experience with statistical software (R, Python, S-Plus, SAS, or similar) and database languages (e.g. SQL) Preferred qualifications: - Master or B.tech in relevant fields Please note that the company offers perks such as Certificate, Letter of recommendation, Flexible work hours, Informal dress code, 5 days a week, and Free snacks & beverages.,

As a Teaching Assistant for the Data Science and Data Analyst Offline Programs, you will have the opportunity to support learners in their journey from foundational analytics to advanced technologies like Deep Learning, NLP, and Generative AI. Your role will involve conducting doubt-clearing sessions, guiding hands-on activities, supporting project development, and creating an engaging learning environment in collaboration with instructors. Key Responsibilities: - Conduct regular doubt-clearing sessions covering various core topics such as Python, statistics, SQL, Excel, data visualization, machine learning, deep learning, NLP, and generative AI. - Organize hands-on exercises, case studies, and model-building challenges using real-world datasets and tools like Pandas, Scikit-learn, Tensorflow, PyTorch, Hugging Face, and OpenAI APIs. - Monitor learner progress, identify gaps, and provide personalized support across foundational and advanced AI concepts. - Foster an engaging classroom environment by encouraging curiosity, experimentation, and collaboration. Sub-Goals: - Strengthen learners" understanding in analytical and AI-driven topics through practice-oriented sessions. - Help students build confidence in handling complex problems using classical and modern AI tools. - Collaborate with instructors to support learners in achieving key milestones such as Exploratory Data Analysis, Machine Learning Projects, NLP Pipelines, and Generative AI Capstone Projects. - Review and provide feedback on assignments involving regression, classification, neural networks, chatbot building, and generative model applications. - Guide learners in developing a diverse portfolio demonstrating skills in data analysis, business problem-solving, and AI innovation. - Ensure students gain hands-on exposure to AI applications like image generation, language modeling, and real-time analytics. Sub-Goals: - Equip students with practical, in-demand skills for roles such as Data Analyst, Business Analyst, Data Scientist, and AI Engineer. - Bridge theoretical knowledge with practical implementation using industry-adopted tools and frameworks. - Maintain batch records, coordinate batch operations, resolve operational issues, and contribute to refining teaching methods for better delivery of advanced AI concepts. Sub-Goals: - Ensure smooth logistics and academic execution across beginner and advanced AI learning tracks. - Contribute actively to improving AI curriculum effectiveness and learner engagement strategies. Qualifications Required: - Education: Bachelor's degree in Computer Science, Engineering, Statistics, or related field (or equivalent industry experience). - Technical Skills: Strong foundation in Python, SQL, Excel, Statistics, data visualization, machine learning. Proficiency in deep learning frameworks, NLP libraries, and generative AI tools. - Hands-on Experience: Developing and deploying ML/DL models, building dashboards, NLP pipelines, and experimenting with generative models. - Communication: Ability to explain fundamental and advanced AI concepts in an engaging way. - Mentorship: Passion for teaching and mentoring learners. - Collaboration & Time Management: Ability to balance academic guidance, operational tasks, and team collaboration effectively. Preferred Qualifications: - Prior experience in mentoring learners in data fields. - Project or teaching experience in deep learning, NLP applications, or generative AI. - Familiarity with collaborative coding, cloud-based notebooks, and APIs for deploying AI solutions. - Participation in AI hackathons, case competitions, or publication of models/projects on platforms like Kaggle or Hugging Face Hub.,

As a Senior Machine Learning Engineer at SettleMint India in Delhi, you will play a crucial role in leading AI & machine learning initiatives within the company. Here's what you can expect in terms of roles, responsibilities, and qualifications: **Role Overview:** You will leverage your extensive experience and expertise to lead AI & machine learning initiatives, collaborating closely with cross-functional teams to identify business problems, design data-driven solutions, and drive actionable insights. **Key Responsibilities:** - Lead and manage the machine learning team, including hiring, performance management, and career development. - Develop and execute the company's machine learning strategy. - Participate in all stages of agile / scrum to design, develop, test, deploy and support machine learning models integrated with different applications. - Apply new ideas and data flow patterns for ease of use, efficiency, and innovation. - Develop AI ML based solutions for various business use cases. - Mentor junior ML engineers on technical competencies. - Generate insights from data sets, identify trends & patterns, and prepare reports for executive and project teams using data visualization. **Qualifications Required:** - Prior proven Machine learning experience of implementing and deploying ML solutions at scale. - Familiarity with classification, clustering, regression, and collaborative filtering. - Demonstrable expertise in Machine Learning, Deep Learning, Image Processing, NLP, predictive & forecasting models. - Experience with AWS SageMaker / Azure ML and advanced SQL. - Hands-on experience with big data technologies such as Hadoop, Spark, and NoSQL. - Proficiency in Python Data Analysis Stack including Pandas, Numpy, and Scikit-learn. - Curiosity to learn and implement latest developments in AI. - Ownership of the MLOps life cycle and model lifecycle management. **Additional Company Details:** At SettleMint, we offer a dynamic work environment where your role will evolve as the company grows. We trust you to execute project deliverables without micro-management, and our work setting is hybrid. We prioritize your learning, training, and development to align with your goals. Additionally, you will have the opportunity to work on global projects and collaborate with global teams, potentially leading to opportunities in our global offices.,

Job Description: As the Team Lead of Distribution Operations team, you will oversee a team responsible for managing AML/KYC and distributor due diligence processes for wholesale and institutional clients of our EMEA-based asset management business. You will work in close partnership with the EMEA Client Management team and act as a key liaison between internal stakeholders and clients, ensuring client-driven activities, processes and outcomes result in an excellent service and experience for our clients. Your primary responsibility will be to ensure we have sufficient information and controls relating to investors in and distributors of our EMEA-based products and strategies, to allow us properly to discharge both our fiduciary duties to our investor universe and our regulatory obligations such as Consumer Duty. You will do this principally by sourcing, analyzing and maintaining relevant client information for operational and regulatory purposes, in many cases working directly with clients. In addition, you will work closely with various other internal functions such as Client Service Ops, Financial Crime Prevention, Global Contract Office and others based both in India and in EMEA. As part of this role, you will be expected to identify opportunities to improve these processes and work with internal teams to deliver these improvements. As the team lead, this role requires strong leadership, stakeholder management, and subject matter expertise in AML/KYC and fund distribution operations. Key Responsibilities: - Team Leadership & Oversight - Lead and mentor a team responsible for managing AML/KYC and distributor due diligence processes. - Allocate tasks, manage workloads, and ensure timely delivery of team objectives. - Provide guidance and support on complex cases, escalations, and regulatory interpretations. - Foster a collaborative and high-performance team culture. - Operational Excellence & Compliance - Oversee the accurate classification of new relationships and ensure distributor status is correctly established. - Ensure AML/KYC and Distributor Due Diligence processes are executed in line with regulatory requirements (e.g., CSSF 18/698, FCA Consumer Duty). - Escalate to Client Managers where necessary to ensure appropriate client engagement. - Escalate to Financial Crime Prevention and / or Distribution & Branch Oversight as necessary to clarify AML/KYC / Distributor Due Diligence requirements and to identify potential alternative types of documentary evidence to meet requirements. - Review and approve documentation and assessments before submission to internal stakeholders or regulators. - Maintain high standards of data accuracy and documentation in systems such as Salesforce and internal repositories. - Stakeholder Engagement - Act as the primary point of contact for internal teams including Client Service Ops, Financial Crime Prevention, and Global Contract Office. - Escalate and resolve issues with appropriate internal teams and governance bodies. - Represent Distribution Operations in cross-functional meetings and committees. - Monitoring & Governance - Ensure timely execution of periodic due diligence and AML/KYC refreshes. - Monitor trigger events and oversee appropriate responses and documentation. - Manage exemptions, extensions, and risk acceptance processes, ensuring governance protocols are followed. - Support branch oversight activities including committee coordination, reporting, and action tracking. - Process Improvement & Controls - Identify and lead initiatives to improve process efficiency, automation, and risk mitigation. - Drive continuous improvement through data analysis, insights, and stakeholder feedback. - Oversee quality control checks and ensure adherence to internal governance standards. Qualifications: Required Qualifications - Bachelors degree in Finance, Business Management, or related field. - 7-10 years of relevant experience, including 2+ years in a leadership or supervisory role. - Strong understanding of AML/KYC regulations and distributor due diligence in asset management. - Excellent communication and stakeholder management skills. - Proven ability to lead teams and manage complex operational processes. - Strong analytical, decision-making, and problem-solving skills. - Proficiency in tools such as Salesforce, Excel, Outlook, and Teams. Preferred Qualifications - Experience in cross-border fund distribution and asset management operations. - Familiarity with regulatory frameworks such as CSSF 18/698 and FCA Consumer Duty. - Experience in process improvement, automation, and data-driven decision-making. - Exposure to governance and committee-level reporting. About Our Company: Ameriprise India LLP has been providing client based financial solutions to help clients plan and achieve their financial objectives for 125 years. We are a U.S. based financial planning company headquartered in Minneapolis with a global presenc

As a highly motivated and experienced data scientist, you will lead a team of Gen-Ai Engineers involved in various processes from data extraction to deploying AI models to production. Your passion for artificial intelligence and staying up-to-date with the latest developments will be crucial in this role. Key Responsibilities: - Utilize frameworks like Langchain for developing scalable and efficient AI solutions. - Integrate vector databases such as Azure Cognitive Search, Weavite, or Pinecone to support AI model functionalities. - Work closely with cross-functional teams to define problem statements and prototype solutions leveraging generative AI. - Ensure robustness, scalability, and reliability of AI systems by implementing best practices in machine learning and software development. - Explore and visualize data to gain an understanding of it, identify differences in data distribution that could affect model performance in the real world. - Oversee data-centered projects, verify data quality, ensure it via data cleaning, and supervise data acquisition process if more data is needed. - Find available datasets online for training, define validation strategies, feature engineering data augmentation pipelines on a given dataset. - Train models, tune hyperparameters, analyze model errors, and design strategies to overcome them. - Deploy models to production. Qualifications and Education Requirements: - Bachelors/Masters degree in computer science, data science, mathematics, or a related field. - 3-10 years of experience in building Gen-Ai applications. Preferred Skills: - Proficiency in statistical techniques such as hypothesis testing, regression analysis, clustering, classification, and time series analysis. - Proficiency with deep learning frameworks like TensorFlow, PyTorch, and Keras. - Specialization in Deep Learning (NLP) and statistical machine learning. - Strong Python skills. - Experience with developing production-grade applications. - Familiarity with Langchain framework and vector databases like Azure Cognitive Search, Weavite, or Pinecone. - Understanding and experience with retrieval algorithms. - Worked on Big data platforms and technologies such as Apache Hadoop, Spark, Kafka, or Hive. - Familiarity with working and deploying applications on Ubuntu/Linux system. - Excellent communication, negotiation, and interpersonal skills.,

As a Senior Data Scientist at our company, you will play a crucial role in developing and implementing machine learning models and algorithms. Your responsibilities will include working closely with project stakeholders to understand requirements, utilizing statistical and machine learning techniques to analyze complex data sets, staying updated with the latest advancements in AI/ML technologies, and collaborating with cross-functional teams to support various AI/ML initiatives. Key Responsibilities: - Develop and implement machine learning models and algorithms. - Work closely with project stakeholders to understand requirements and translate them into deliverables. - Utilize statistical and machine learning techniques to analyze and interpret complex data sets. - Stay updated with the latest advancements in AI/ML technologies and methodologies. - Collaborate with cross-functional teams to support various AI/ML initiatives. Qualifications: - Bachelor's degree in Computer Science, Data Science, or a related field. - Strong understanding of machine learning, deep learning, and Generative AI concepts. Preferred Skills: - Experience in machine learning techniques such as Regression, Classification, Predictive modeling, Clustering, Deep Learning stack using Python. - Experience with cloud infrastructure for AI/ML on AWS (Sagemaker, Quicksight, Athena, Glue). - Expertise in building enterprise-grade, secure data ingestion pipelines for unstructured data (ETL/ELT) including indexing, search, and advance retrieval patterns. - Proficiency in Python, TypeScript, NodeJS, ReactJS (and equivalent) and frameworks (e.g., pandas, NumPy, scikit-learn, SKLearn, OpenCV, SciPy), Glue crawler, ETL. - Experience with data visualization tools (e.g., Matplotlib, Seaborn, Quicksight). - Knowledge of deep learning frameworks (e.g., TensorFlow, Keras, PyTorch). - Experience with version control systems (e.g., Git, CodeCommit). - Strong knowledge and experience in Generative AI/LLM based development. - Strong experience working with key LLM models APIs (e.g. AWS Bedrock, Azure Open AI/OpenAI) and LLM Frameworks (e.g. LangChain, LlamaIndex). - Knowledge of effective text chunking techniques for optimal processing and indexing of large documents or datasets. - Proficiency in generating and working with text embeddings with understanding of embedding spaces and their applications in semantic search and information retrieval. - Experience with RAG concepts and fundamentals (VectorDBs, AWS OpenSearch, semantic search, etc.), Expertise in implementing RAG systems that combine knowledge bases with Generative AI models. - Knowledge of training and fine-tuning Foundation Models (Athropic, Claud, Mistral, etc.), including multimodal inputs and outputs. Good To Have Skills: - Knowledge and Experience in building knowledge graphs in production. - Understanding of multi-agent systems and their applications in complex problem-solving scenarios. Please note that Pentair is an Equal Opportunity Employer, and we value diversity in our workforce as it brings different perspectives and creative ideas that contribute to our continuous improvement.,