77,961 Data Science Jobs in Bid

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.

Designation: AM / MT Data Science (Data Analyst) Location: Mumbai  Work Experience: 0.6 months to 3 years Qualification: Bachelors or Masters degree in Engineering,Statistics, Mathematics, Computer Science or related fields roles and responsibilities Data Analysis & Exploration: Analyse structured and unstructured data to identify trends, patterns and actionable insights Perform data profiling, cleaning and transformation Assist in developing dashboards, visual stories using tools like TableauModel development support: Collaborate with Data scientist in Feature engineering, data cleanup / transformation and modelevaluation Support testing and validation of ML/AI models using Python Help interpret model output and translate results for businessBusiness Understanding and Insights: Participate in discussions with business to understand business problems Document, track and report the progress Help in defining the metrics and evaluating impact of AI/ML models post deploymentAI initiatives (not mandatory) Support GenAI workflows (Prompt engineering, annotation, evaluation) Assist in model testing, output comparison or basic RAG pipeline use cases Required Skills Bachelors or Masters degree in Engineering, Statistics, Mathematics, Computer Science or related fields Strong Knowledge of Excel, Google Sheets and SQL Familiarity with Python (Pandas, NumPy, Matplotlib) Analytics and problem solving mindset Understanding of basic ML concepts, Jupyter notebooks etc. Awareness of NLP/LLM concepts (not mandatory)  

About ExcelR: ExcelR is a leading edtech company founded by distinguished alumni of IIM and ISB, dedicated to transforming careers through world-class upskilling. Recognized twice with the Deloitte Fast 50 Award, ExcelR is one of Indias fastest-growing tech companies. With an employee size of 450+, we have a strong PAN India and USA presence. With a thriving community of 300,000+ learners, ExcelR delivers impactful learning experiences across the globe. We proudly collaborate with premier institutes like IIT Madras, IIT Jammu, IIT Roorkee, and BITS Pilani, offering cutting-edge programs. Job Title: Data science Trainer Job Description: We are looking for a seasoned professional with in-depth expertise as a Data scientist. The ideal candidate should have a proven track record of hands-on experience with related field technologies, including managing complex projects, mentoring teams, and driving operational excellence in the field. Strong grasp of Python/R, Machine Learning, and statistical modeling Experience with data preprocessing, EDA, and model building Familiarity with libraries like NumPy, pandas, scikit-learn, and TensorFlow Proficiency in deploying models and working with real-world datasets Key Responsibilities: Develop, deliver, and continuously enhance training content and educational programs. Mentor and train junior in-house trainers, ensuring high-quality instruction across teams. Supervise the planning, execution, and evaluation of internships, assignments, and training programs. Innovate and maintain cutting-edge educational materials and content. Ideal Candidate Profile Demonstrated expertise in the relevant domain with industry experience Excellent communication and presentation abilities to deliver impactful training Passion for teaching and mentoring aspiring professionals Qualifications Prior experience in training, mentoring, or educational roles Strong interpersonal and time management skills Ability to collaborate effectively in a team environment Certifications in relevant subject areas or instructional design If youre an innovative, highly skilled professional with a passion for both technology and education, wed love to hear from you! Conditions:  Batch Management: Handle 3 batches consecutively, with assignments based on business requirements. This could include weekday/weekend and classroom batches.  Demos & Webinars: Conducting demo sessions and webinars.  Doubts Clarification Sessions: Organizing sessions to address and clarify students' doubts.  Course Material Preparation: Develop various teaching materials including presentations, assignments, projects, quizzes, and other relevant content.  Project Mentoring: Offer guidance and mentor-ship for student projects.  Placement Preparation: Assist students in preparing for placements, including conducting mock interviews.  Customer Query Handling: Addressing queries from potential customers.  Additional Responsibilities: Need to undertake other tasks as per the business requirement.

Job Title: GenAI Technical Support Advisory Lead L25 Support Layer Location: India Remote or India Office Work Hours: US Time Zone Active until 300 PM PST Role Overview We are looking for a handson leader with expertise in Generative AI and enterprise AI chat technologies who can serve as an L25 support layer bridging the gap between frontline support L2 and deep technical experts L3 This person will act as the first point of escalation for AIrelated technical questions ensure quality in responses and coordinate with global colleagues to resolve complex queries This role is part technical support part advisory ensuring internal teams have the right AI tools workflows and knowledge to work effectively Key Responsibilities Serve as the primary point of contact for escalated technical queries related to Generative AI GenAI the internal enterprise AI chat solution and AIassisted workflows Provide direct technical assistance and guidance to users escalate to and collaborate with L3 subjectmatter experts when necessary Ensure accuracy consistency and quality in responses provided to internal teams Document solutions best practices and repeatable workflows for common queries Monitor and analyze support requests to identify training opportunities system improvements or process optimizations Stay updated on emerging AI tools prompt engineering techniques and integration capabilities Required Qualifications Proven experience in Generative AI technologies including enterprise AI chat solutions eg Azure OpenAI Anthropic Claude Google Gemini or custom internal AI chat platforms Strong technical troubleshooting and problemsolving skills especially in complex AI workflows Excellent communication skills with the ability to explain technical concepts clearly to nontechnical audiences Experience acting in an L25 role or similar owning escalations and bridging between support and engineering teams Proactive resourceful and comfortable working across time zones Strong documentation and knowledge management skills Preferred Qualifications Experience working in a technology support or AI advisory role Familiarity with AI integration platforms eg n8n Zapier Workato or workflow automation tools Exposure to prompt engineering best practices

About the Role This is an exciting software engineer role reporting to the Senior Engineering Manager. You will engineer innovative applications and services using Generative AI GenAI You will work with cutting edge technologies creating new experiences and services Key Responsibilities Engineer well architected efficient scalable stable and secure web applications and backend services with an emphasis on APIs and backend services Develop scalable Generative AI systems that can be used across multiple projects and platforms Stay UpToDate with modern software engineering practices procedures and paradigms and apply this knowledge to software Collaborate with an international engineering and product team Experience Please note that you do not need to qualify for all requirements to be considered We encourage you to apply if you can meet most of the requirements and are comfortable opening a dialogue to be considered Bachelor Masters degree in Computer Science Computer Engineering or related field or equivalent experience Python experience GenAI concepts knowledge JS or similar technologies backend Java NET hyperscale's Google Cloud Azure, AWS and have Python experience Experience working with VCS tools such as GIT Experienced in branching merging and building CICD pipelines Experience with security protocols such as oAuth Microsoft Entra ID SSO Okta and securing applications using them, Experience to development and deployment of applications using Docker Kubernetes. Experience working with varied integration patterns REST SOAP gRPC Web Sockets Batch Webhooks Handson experience creating unit test cases integration test cases perform code reviews, Experience managing version control solutions static code analysis and performing code reviews You have experience with load testing troubleshooting and optimizing performance of web services, Clear communication and excellent problem-solving skills, Enjoy working independently and in a team environment Beneficial Experience Experience using Generative AI software engineering solutions such as Cursor Git, Hub CoPilot, Knowledge of reinforcement learning natural language processing and other advanced AI techniques Experience with cloud based AI services and IaaC such as Terraform and Ansible, You have experience working in large data driven services Experience with Generative AI solutions such as Azure AI Studio AWS Bedrock and Hugging Face

Required Skills & Qualifications Hands-on experience with time series analysis and cost modelling. Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. Knowledge of optimisation algorithms and business strategy modelling.

Sr Python Gen AI engineers Job Summary Develop generative AI solutions on AWS focusing on LLMs prompt engineering RAG and agentic AI using n8n and Python libraries like LangChain Key Requirements 8 Points 1Build LLMs eg Anthropic Claude on AWS Bedrock with boto3 2Finetune LLMs on AWS SageMaker using transformers and LoRA 3Create prompts with langchain for optimized LLM outputs 4Develop RAG pipelines with AWS OpenSearch and langchain 5Build AI agents with crewai or autogen on AWS Lambda 6Implement agentic workflows in n8n eg n8nioworkflows6270 7Deploy apps with Docker on Amazon ECSEKS 8Monitor performance with Amazon CloudWatch and wandb MustHave Skills 5 years Python experience with 2years in GenAILLMs Expertise in AWS Bedrock SageMaker Lambda boto3 Proficiency in transformers langchain crewai autogen wandb Experience with n8n workflows RAG prompt engineering Preferred Skills AWS certification Machine LearningSolutions Architect Familiarity with llamaindex n8n templates

Sr Python Gen AI engineers Job Summary Develop generative AI solutions on AWS focusing on LLMs prompt engineering RAG and agentic AI using n8n and Python libraries like LangChain Key Requirements 8 Points 1) Build LLMs eg Anthropic Claude on AWS Bedrock with boto3 2) Finetune LLMs on AWS SageMaker using transformers and LoRA 3) Create prompts with langchain for optimized LLM outputs 4) Develop RAG pipelines with AWS OpenSearch and langchain 5) Build AI agents with crewai or autogen on AWS Lambda 6) Implement agentic workflows in n8n eg n8nioworkflows6270 7) Deploy apps with Docker on Amazon ECSEKS 8) Monitor performance with Amazon CloudWatch and wandb Must Have Skills 5 years Python experience with 2years in GenAILLMs Expertise in AWS Bedrock SageMaker Lambda boto3 Proficiency in transformers langchain crewai autogen wandb Experience with n8n workflows RAG prompt engineering Preferred Skills AWS certification Machine LearningSolutions Architect Familiarity with llamaindex n8n templates

Technical Business Analyst to drive the successful launch of a digital assistant within our IT support Slack channels This role will analyze employee interactions coordinate crossfunctional teams and ensure the delivery of highquality knowledge articles and automated solutions to enhance our IT support experience Key Responsibilities Analyze IT support Slack channels to identify common employee requests pain points and automation opportunities Collaborate with IT teams to design and implement and comprehensive knowledge articles for the digital assistant and support engineering teams with knowledge data to support agentic actionbased solutions Author review and maintain clear concise and accurate knowledge articles to support automated resolutions Coordinate and provide quality control over high volumes of knowledge articles produced by other teams ensuring consistency and accuracy Act as a project coordinator managing timelines deliverables and communication across multiple teams to ensure a smooth digital assistant launch Gather and document business requirements user stories and process flows to inform solution design Monitor digital assistant performance postlaunch analyze feedback and recommend continuous improvements Champion best practices in conversational design user experience and IT support automation Must be able to work under own initiative delivering high quality results in a very fast paced environment oWe have 20 Support channels each with 1000 unique requests per month and we want to launch a highquality digital assistant in a different support channel every month from August 2025 Design and maintain structured knowledge models and metadata frameworks optimized for GenAI and LLM technologies eg RAGbased architectures Core Skills Required Business Analysis Requirements gathering process mapping gap analysis and translating business needs into technical solutions Data Analysis Ability to analyze large volumes of unstructured data eg Slack conversations to identify trends and automation opportunities Technical Documentation Writing editing and maintaining clear and concise knowledge articles and technical documentation Project Coordination Managing timelines deliverables and crossteam collaboration Quality Assurance Reviewing and validating content and solutions for accuracy consistency and effectiveness Stakeholder Management Engaging with diverse teams IT Knowledge Management Digital Experience etc and managing expectations Change Management Supporting adoption and training for new digital assistant solutions Communication Strong verbal and written communication skills for both technical and nontechnical audiences Problem Solving Proactive approach to identifying issues and proposing effective solutions User Experience UX Understanding of conversational design and usercentric solution development AISpecific Skills Required Conversational AI Design Experience designing testing and optimizing chatbot or digital assistant conversations and flows Natural Language Processing NLP Understanding of NLP concepts intent recognition and entity extraction AI Training Tuning Ability to train AI models using realworld data refine intents and improve accuracy over time Bot Frameworks Platforms Familiarity with platforms such as Dialogflow Microsoft Bot Framework IBM Watson or similar Integration Skills Experience integrating digital assistants with ITSM tools eg ServiceNow APIs and knowledge bases Analytics Monitoring Ability to use analytics tools to monitor bot performance user satisfaction and identify areas for improvement Content Governance Understanding of how to structure and govern knowledge for optimal AI consumption and retrieval Security Compliance Awareness of data privacy security and compliance considerations in deploying AI solutions at scale Experience with knowledge management platforms ServiceNow Knowledge Base Confluence SharePoint etc Understanding of AIGenAI technologies particularly related to large language models LLMs and retrievalaugmented generation RAG Strong data organization skills including taxonomies metadata standards and information architecture Attributes Experience for a Senior Highly Experienced Candidate Leadership Demonstrated ability to lead crossfunctional teams and drive largescale digital transformation initiatives Strategic Vision Experience developing and executing a roadmap for digital assistant implementation in a complex organization Change Agent Proven track record of championing new technologies and driving adoption across diverse user groups Depth of Experience 7 years in business analysis IT transformation or digital experience roles with at least 3 years working directly with AI or digi

As a Senior Specialist in Global Data Science at Colgate-Palmolive, you will play a crucial role in leading projects within the Analytics Continuum by conceptualizing and building machine learning, predictive modeling, simulations, and optimization solutions. Your focus will be on addressing business questions with recommended actions that have a significant impact on the business, allowing for scalability across markets. **Key Responsibilities:** - Conceptualize and build predictive modeling, simulations, and optimization solutions to address business questions or use cases - Apply machine learning and AI algorithms to analytics to develop inferential and predictive models for scalable solutions - Develop end-to-end business solutions from data extraction to statistical modeling, and present findings in an easily interpretable manner - Conduct model validations, continuous improvement, and deployment of models using Airflow and Docker on Google Cloud Platforms - Manage Pricing and Promotion, Marketing Mix projects from scoping to delivery - Study large datasets to identify trends and patterns, mine data using technologies like BigQuery and SQL - Create visualizations using tools like Looker, PyDash, Flask, PlotLy, and streamlit - Collaborate closely with business partners across different geographies **Qualifications Required:** - BE/BTECH in Computer Science or Information Technology, MBA or PGDM in Business Analytics/Data Science, or related fields - Additional certifications or courses in Data Science - 5+ years of experience in building statistical models and deriving insights - Proficiency in Python and SQL for coding - Experience with GitHub, Airflow, and visualization frameworks - Strong understanding of Cloud Frameworks like Google Cloud, Snowflake, and services like Kubernetes - Experience in a client-facing role, working in a dynamic environment **Additional Company Details:** Colgate-Palmolive is committed to fostering an inclusive environment where individuals with diverse backgrounds and perspectives can thrive. The company values developing talent with a true sense of belonging and ensuring that every individual can contribute meaningfully to the business. Colgate-Palmolive is an Equal Opportunity Employer offering reasonable accommodation during the application process for persons with disabilities.,

As a Data Scientist- Analyst/Senior Analyst, your role involves conducting insight reviews through advanced analytics using internal and external data sources. You will utilize sophisticated predictive modeling to understand necessary changes for improvement and consider impacts from operational and client change requests for benefit realization. Your responsibilities include leading the insight direction to align with operational strategy, collaborating with shared services MI teams to consolidate disparate data sets, and providing intelligent insights through data analysis for business and client requirements. Additionally, you will support senior management in formulating management information and insight to inform business decisions and budget assumptions. Key Responsibilities: - Conducting insight reviews through advanced analytics - Utilizing predictive modeling for improvement understanding - Considering impacts from operational and client change requests - Leading insight direction to align with operational strategy - Collaborating with shared services MI teams for data consolidation - Providing intelligent insights for business and client requirements - Supporting senior management in formulating management information and insight - Leading projects by analyzing data and converting it into actionable insights - Working with BI teams to deliver services to clients in a robust and governed manner - Flexibility to work in rotational shifts Qualifications Required: - Bachelor's Degree - 2-8 years of experience as a Data Scientist - Skills in Data Science, AI, ML, Python, AWS - Industry experience in ITES/BPO/KPO Please note the Job Code: GO/JC/1116/2025. In case of any queries, you can reach out to the recruiter Marilakshmi S.,

As a motivated and highly skilled Data Scientist joining the Flight Safety team, your role will be crucial in utilizing advanced analytics and machine learning techniques to drive safety-related decisions and enhance operational processes. You will primarily focus on analyzing time-series and multivariate data to detect anomalies, identify patterns, and create predictive models that contribute to improving flight safety and minimizing risks. - Conduct exploratory data analysis to reveal insights from complex datasets - Apply advanced anomaly detection techniques to spot irregularities and potential safety risks - Develop machine learning and deep learning models like ANN, RNN, and CNN for predictive safety analytics - Support data-driven decision-making within the field of flight safety using big data analytics tools and AI/ML frameworks - Design custom algorithms tailored to meet specific domain requirements with precision and reliability - Write efficient, maintainable code in Python and MATLAB for data processing, modeling, and algorithm deployment - Collaborate with cross-functional teams to translate analytical findings into actionable safety initiatives To qualify for this role, you should: - Hold a Bachelor's degree in Engineering with a specialization in Data Science or a related field - Have certification in Data Science - Possess a minimum of 6 years of practical experience in data science, machine learning, or analytics roles - Have a proven track record in developing AI/ML models, particularly in anomaly detection and predictive analytics - Demonstrate proficiency in data analysis, exploratory data analysis, anomaly detection (time-series & multivariate data), machine learning, deep learning, big data analytics, and AI-driven risk forecasting - Showcase strong programming skills in Python and MATLAB - Exhibit expertise in custom algorithm design, data collection, preprocessing, and integration By joining the team, you will have the opportunity to contribute to cutting-edge data science projects in the aviation safety sector, work in a collaborative and innovation-oriented environment, and be part of a mission-critical team dedicated to predictive safety and operational excellence. (Note: The additional details of the company were not present in the provided job description),

As a Data Scientist at our company, your role will involve the following key responsibilities: - Business & Strategy Alignment - Proactively engage with business stakeholders, product managers, and domain experts to deeply understand key organizational challenges and strategic goals. - Formulate and scope data science initiatives, defining clear objectives, success metrics, and a technical roadmap that directly addresses identified business requirements. - End-to-End Model Development & Deployment - Design, prototype, build, and validate machine learning and statistical models from scratch, without reliance on pre-packaged solutions. - Implement and manage MLOps pipelines within Azure Machine Learning to ensure reproducible model training, versioning, testing, and continuous deployment into live operational environments. - Collaborate with DevOps and engineering teams to ensure algorithms run efficiently and scale reliably within the cloud environment. - Data Engineering & Feature Management - Execute complex data ingestion, exploration, and feature engineering tasks, applying rigorous statistical methods and domain knowledge to raw and disparate datasets. - Ensure data integrity throughout the modeling lifecycle, performing extensive Exploratory Data Analysis (EDA) and cleaning to prepare high-quality inputs. - Advanced AI & Innovation (Preferred/Plus) - Explore, experiment with, and deploy large language models (LLMs) and other Gen AI techniques to create new products or optimize existing processes. - Investigate and prototype intelligent software agents capable of autonomous decision-making, planning, and tool use, moving beyond simple predictive models. - Code Quality & Collaboration - Write clean, well-documented, and efficient Python code, adhering to software engineering best practices, including unit testing and code reviews. - Mentor junior team members and contribute to the growth of the team's overall ML/AI knowledge base. Required Qualifications: - Education: Master's degree or higher in Computer Science, Statistics, Mathematics, or a related quantitative field. - Programming Mastery: 5+ years of professional experience leveraging Python for data science, including deep expertise in the PyData stack (e.g., Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch). - Cloud ML Platforms: Proven, hands-on experience building and managing ML models and MLOps workflows specifically using Azure Machine Learning services. - Statistical Rigor: Strong background in statistical modeling, experimental design (A/B testing), and model validation techniques. - Data Skills: Expert proficiency in SQL and experience working with large-scale, high-velocity data, including ETL/ELT processes and data visualization. Preferred Qualifications (A Significant Plus): - Generative AI Experience: Practical experience fine-tuning, RAG-ifying, or deploying modern Large Language Models (LLMs). - Agent Development: Knowledge of agentic frameworks and experience designing multi-step, tool-using autonomous AI workflows. - Experience with other cloud platforms (AWS Sagemaker, GCP Vertex AI) is beneficial. - Demonstrated ability to write production-level, highly optimized code for critical systems.,

As a senior data scientist at UBS, you will play a pivotal role in driving digital transformation by working on data science projects within the newly established Data and Analytics Team in Group Legal. Your responsibilities will include: - Collaborating with various stakeholders to translate reporting requirements into actionable tasks and implement product enhancements. - Designing, building, and deploying high-performance AI/ML/NLP models to meet business objectives. - Monitoring and optimizing model performance to ensure quality, stability, and scalability. - Cleaning, manipulating, and processing raw data into useful information suitable for business purposes. - Validating AI/ML opportunities, defining business cases, and creating roadmaps for implementation. - Documenting model performance, governance, and validation processes comprehensively. - Mentoring and guiding junior data scientists and analysts to foster technical excellence across the team. To excel in this role, you should possess the following qualifications: - Minimum of 3 years of experience delivering data science projects in a leading consultancy or at a large organization. - Proficiency in developing end-to-end ML and NLP solutions, including data sourcing, feature engineering, model training, evaluation, and visualization. - Experience in state-of-the-art ML algorithms and techniques, such as XGBoost, Neural Networks, supervised, unsupervised, or reinforcement learning. - Proficiency in building ML & NLP / LLM solutions using common ML libraries and frameworks like Pandas, Sklearn, TensorFlow, Transformers, OpenAI, Huggingface. - Hands-on experience with NLP applications such as named entity recognition, text classification, sentiment analysis, or chatbot development. - Familiarity with MLOps practices, containerized solutions like Docker, Kubernetes, and cloud platforms such as Azure, AWS, or Google Cloud. - Ability to explain technical concepts to non-technical stakeholders. - Strong team player and communicator. UBS is the world's largest and the only truly global wealth manager, operating through four business divisions: Global Wealth Management, Personal & Corporate Banking, Asset Management, and the Investment Bank. With a presence in over 50 countries, UBS offers flexible ways of working and a purpose-led culture that fosters collaboration and innovation. UBS is an Equal Opportunity Employer that values diversity and empowers individuals from various backgrounds. If you are looking to make an impact and be part of a dynamic team, consider joining #teamUBS. UBS welcomes applications from career returners. Learn more about the Career Comeback program on ubs.com/careercomeback.,

Role Overview: At Lilly, we are looking for a highly skilled Data Scientist with 7-8 years of experience or an advanced degree (Masters/Ph.D.) in Statistics, Machine Learning, or Data Science. The ideal candidate should be passionate about solving complex business challenges in manufacturing and supply chain domains through advanced analytics. This role requires expertise in statistical modelling, machine learning, time-series analysis, and simulation techniques, along with the ability to manage large datasets and derive actionable insights. Proficiency in Python/R programming and familiarity with optimization techniques are essential. The candidate must be able to translate business problems into technical solutions, communicate effectively with stakeholders, and adapt to evolving business needs while simplifying technical concepts for non-technical audiences. Key Responsibilities: - Design and develop advanced analytics solutions using statistics, machine learning, data science, and optimization methods for solving various problems such as anomaly detection, time series forecasting, root cause analysis, and predictive maintenance. - Apply data visualization techniques for effective storytelling through data and share insights with business leaders. - Conduct exploratory data analysis and feature engineering on structured, semi-structured, and unstructured data. - Integrate and manage diverse datasets ensuring robustness for high-dimensional, imbalanced, and noisy data. - Develop scalable solutions for real-time inference, batch processing, and edge computing using modern deployment tools. - Lead end-to-end model lifecycle including development, deployment, monitoring, and performance optimization. - Stay updated with emerging AI/ML research and implement practical innovations. - Collaborate with cross-functional teams as a trusted advisor and ensure best practices in version control and CI/CD workflows. Qualification Required: - B.Tech./Masters/Ph.D. in statistics, Machine Learning, Data Science, or a related field. Additional Details: Lilly has pioneered the development of significant drugs and treatments over the years with a strong pipeline. The company's focus on using new-gen technologies helps redefine what is possible through technology in pharma. Lilly encourages a commitment to making a real difference in lives and provides a platform for the best talent to innovate and accelerate together. Employees at Lilly are dedicated to making a significant difference in the well-being of people worldwide.,

You are seeking a highly skilled and experienced Senior Data Scientist to join your team. The ideal candidate will have a strong background in data science, machine learning, and statistical analysis. As a Senior Data Scientist, you will be responsible for leading data-driven projects, developing predictive models, and providing actionable insights to drive business decisions. - Lead and manage data science projects from conception to deployment. - Develop and implement machine learning models and algorithms to solve complex business problems. - Analyze large datasets to identify trends, patterns, and insights. - Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions. - Communicate findings and recommendations to stakeholders through reports, presentations, and visualizations. - Stay up to date with the latest advancements in data science and machine learning technologies. Qualifications: - Bachelor's or Master's in Data Science, Computer Science, Statistics, or a related field. - 4+ years of experience. - Expertise in big data & computing technologies like Apache Spark. Expertise in Apache Ray is a plus. - Strong proficiency in programming languages such as Python or R, SQL. - Experience with machine learning frameworks and libraries. - Proven experience with Microsoft Azure. - Excellent analytical and problem-solving skills. - Ability to work independently and as part of a team. - Strong communication and presentation skills. Preferred Qualifications: - Experience in building forecasting systems using statistical and machine learning algorithms. - Experience with mathematical optimization using Gurobi. - Familiarity with data visualization tools (Power BI, Streamlit, Dash). - Familiarity with the industrial or construction supply industry.,

Role Overview: You are looking for a highly experienced and versatile Data Scientist with a minimum of 5 years of experience, specializing in Generative AI. In this dual-role position, you will be involved in advanced data science and AI projects, specifically focusing on applications of Generative AI. Additionally, you will play a crucial role in training programs, workshops, and knowledge-sharing sessions. Key Responsibilities: - Possess strong hands-on expertise in Generative AI - Teach and mentor others in the field - Build and deploy AI models - Design engaging educational experiences - Work on cutting-edge projects - Contribute to educational initiatives - Share knowledge with others in the field Qualifications Required: - Minimum of 5 years of experience in Data Science - Specialization in Generative AI - Proven ability to teach and mentor others - Comfortable with building and deploying AI models - Strong communication and knowledge-sharing skills,

Role Overview: Join the Data Science and Artificial Intelligence Team at Hitachi Solutions to fast-track your career in a disruptive startup atmosphere. As a Data Scientist, you will have the opportunity to work with a team of fun and nerdy colleagues focused on hypergrowth and engineering excellence. Your main goal will be to transform the company into a billion-dollar product company by making the cloud easier for customers. Key Responsibilities: - Execute tasks with a bias towards action, set high standards, collaborate with teams, and think boldly - Continuously learn new techniques and technologies, pushing the practice forward - Design and deploy end-to-end AI systems and pipelines - Communicate clearly with clients and peers - Gather requirements from business stakeholders to solve problems and translate them into solutions - Manage time effectively, set client expectations, and deliver quality work within deadlines Qualifications: - Master's Degree in Computer Science, Data Science, or related fields, or equivalent professional experience - Experience working with cloud technologies like Azure Databricks and MLflow on the Azure stack - Strong interpersonal and communication skills to explain technical concepts to non-technical audiences - Ability to work independently, collaborate in diverse teams, prioritize tasks, and thrive in a fast-paced environment - Proficiency in various modeling algorithms, feature engineering, model evaluation, and EDA - Strong programming skills in Python/PySpark and SQL - Understanding of distributed systems and the ability to build models for different serving environments (Note: Additional company information was not provided in the job description),

You are seeking an exciting opportunity to be part of a dynamic and growing team in a fast-paced and challenging environment. This unique role offers you the chance to collaborate with the Business team in providing a comprehensive perspective. As a Data Scientist Analyst in Asset and Wealth Management Risk within our AWM Risk team, you will play a key role in innovating and implementing data-driven risk analytics solutions through advanced data science and machine learning techniques. Your contributions will enable us to enhance our operations, strengthen our core values, and expand our analytical capabilities to support the growth of Newton's platform. JPMorgan Asset & Wealth Management Risk (AWM) is looking for a skilled Risk professional with quantitative analysis expertise to join our AWM Risk Analytics team. This team, part of AWM Risk Management, consists of innovative professionals focused on quantitative and market risk. You will be involved in developing risk measurement methodologies, analytics calculations, and maintaining the AWM Risk System (Newton) used by AWM Risk Management and Front Office stakeholders. Responsibilities: - Collaborate with peers and stakeholders to identify opportunities for using Data Science to drive value and enhance security and portfolio risk analytics. - Lead enhancements in AI/ML and statistical techniques for data and analytics validation. - Design and deliver scalable solutions using cutting-edge technologies like AI and LLMs. - Analyze large data sets, follow best practices for data model and architecture, and contribute to risk methodology enhancement. Required Qualifications: - Minimum 6 months of experience as a Data Scientist or in a related quantitative role. - Strong quantitative skills, attention to detail, ability to multitask, and work independently. - Excellent communication skills. - Proficiency in statistics, AI/ML techniques, and problem-solving. - Knowledge of programming languages such as SQL, Python, ML, AWS Sagemaker, TensorFlow, etc. Preferred Qualifications: - Experience in financial markets or quantitative analysis within Risk Management or Front Office. - Familiarity with asset pricing, VaR backtesting, and model performance testing.,