1 Panda Jobs nearby Tiruchirappalli

As an AI/ML Engineer at our company, you will be responsible for designing, developing, and deploying ML models and AI-driven solutions. You will work onsite in Trichy and must be based in our Trichy office as remote work is not an option. Key Responsibilities: - Develop and deploy machine learning models and AI-based solutions. - Preprocess, clean, and analyze large datasets. - Optimize ML pipelines for scalability and efficiency. - Work with cloud platforms and MLOps tools for deployment and monitoring. - Collaborate with teams to integrate AI solutions into business workflows. - Stay updated with advancements in AI/ML technologies. Required Skills & Qualifications: - Bachelor's/Master's in Computer Science, Data Science, AI/ML, or related field. - 5+ years of hands-on experience in AI/ML development. - Strong Python skills and experience with TensorFlow, PyTorch, and Scikit-learn. - Experience with AWS, GCP, or Azure for AI/ML workloads. - Proficiency in data processing with Pandas, NumPy, and SQL. - Experience with MLOps tools like MLflow, Kubeflow, or TensorBoard. - Strong problem-solving and model optimization skills. - Excellent communication and collaboration skills. - Must work from the Trichy office. Remote work is not an option. Preferred Qualifications: - Experience with NLP and Computer Vision. - Exposure to Generative AI models and LLMs. - Understanding of AI ethics and responsible AI practices. - Knowledge of DevOps and CI/CD pipelines for ML deployment.,

Role Overview: You will be responsible for fetching and transforming data from various systems, conducting in-depth analyses to identify gaps, opportunities, and insights, and providing recommendations that support strategic business decisions. Key Responsibilities: - Data Extraction and Transformation: - Fetch data from multiple systems, transform it to create a unified dataset, and ensure data accuracy. - Data Analysis and Insight Generation: - Analyze large datasets to identify patterns, gaps, and trends. - Develop actionable insights and recommendations that support business objectives. - Visualization and Reporting: - Create impactful visualizations and reports to effectively communicate findings to stakeholders. - Collaboration: - Partner with cross-functional teams to align analytical projects with business goals and translate findings into strategic recommendations. Qualification Required: - Academic Qualifications & Experience Required: - Bachelors or Masters degree in Applied Mathematics, Management Science, Data Science, Statistics, Econometrics, or Engineering. - Extensive experience in Data Lake architecture, building data pipelines using AWS services like EC2, Lambda, Redshift, Glue, Athena, CloudWatch, and S3. - Must be proficient in Python and SQL. - Experience in the banking domain. - High motivation, good work ethic, maturity, and personal initiative. - Strong oral and written communication skills. Additional Details: The company is focused on AI & Data Science Enterprise Delivery and you will be reporting to the VP Business Growth. External stakeholders you will be working with are Clients.,

As a Data Engineer at BuildingBlocks, you will play a crucial role in owning the data pipeline that powers our LLM training and fine-tuning process. Your responsibilities will involve designing ETL pipelines for text, PDFs, and structured data, implementing data deduplication, filtering, and normalization, training and managing tokenizers, building datasets for supervised fine-tuning and evaluation, and collaborating closely with domain experts to generate instruction/response pairs. Key Responsibilities: - Design ETL pipelines for text, PDFs, and structured data. - Implement data deduplication, filtering (toxicity, PII), and normalization. - Train and manage tokenizers (SentencePiece/BPE). - Build datasets for supervised fine-tuning and evaluation. - Work closely with domain experts to generate instruction/response pairs. Qualifications Required: - Strong proficiency in Python, SQL, and data wrangling frameworks (Pandas, Spark). - Experience working with large text datasets, cleaning, and preprocessing. - Familiarity with NLP-specific preprocessing techniques such as chunking and embeddings. - Knowledge of cloud data storage platforms like S3, GCS, and Blob. - Bonus: Prior experience in AI/ML pipelines. About BuildingBlocks: At BuildingBlocks, our diverse team shares a common mission of creating beautiful experiences that have a positive impact on people's lives and the businesses we serve. Our culture is rooted in purpose, blending genuine human connection with a meticulous approach to our craft. We are a company that embraces youthfulness, fun, defiance, boldness, and drive to make a significant mark in the industry. As a Data Engineer at BuildingBlocks, you will play a crucial role in owning the data pipeline that powers our LLM training and fine-tuning process. Your responsibilities will involve designing ETL pipelines for text, PDFs, and structured data, implementing data deduplication, filtering, and normalization, training and managing tokenizers, building datasets for supervised fine-tuning and evaluation, and collaborating closely with domain experts to generate instruction/response pairs. Key Responsibilities: - Design ETL pipelines for text, PDFs, and structured data. - Implement data deduplication, filtering (toxicity, PII), and normalization. - Train and manage tokenizers (SentencePiece/BPE). - Build datasets for supervised fine-tuning and evaluation. - Work closely with domain experts to generate instruction/response pairs. Qualifications Required: - Strong proficiency in Python, SQL, and data wrangling frameworks (Pandas, Spark). - Experience working with large text datasets, cleaning, and preprocessing. - Familiarity with NLP-specific preprocessing techniques such as chunking and embeddings. - Knowledge of cloud data storage platforms like S3, GCS, and Blob. - Bonus: Prior experience in AI/ML pipelines. About BuildingBlocks: At BuildingBlocks, our diverse team shares a common mission of creating beautiful experiences that have a positive impact on people's lives and the businesses we serve. Our culture is rooted in purpose, blending genuine human connection with a meticulous approach to our craft. We are a company that embraces youthfulness, fun, defiance, boldness, and drive to make a significant mark in the industry.

In this role at Miratech, you will be working with Large Language Models (LLMs) to design, develop, and integrate advanced AI solutions within the platform. Your focus will be on automating data processing, generating actionable insights, and enhancing decision-making workflows through natural language understanding. **Responsibilities:** - Design, develop, and optimize NLP models for text processing, classification, and information extraction. - Apply machine learning and AI techniques to address real-world business problems. - Utilize DBT, Snowflake, and Airflow to create robust and scalable data pipelines that support ML workflows. - Conduct exploratory data analysis (EDA), feature engineering, and model evaluation. - Deploy and monitor models in production, ensuring performance and scalability. - Collaborate with cross-functional teams to translate requirements into actionable AI/ML solutions. - Document processes, models, and workflows to uphold reproducibility and knowledge sharing standards. **Qualifications:** - 2+ years of hands-on experience in NLP, Machine Learning, and AI. - Strong programming skills in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, SpaCy, NLTK, or HuggingFace). - Solid understanding of data modeling, ETL pipelines, and SQL. - Experience with DBT, Snowflake, and Airflow. - Familiarity with MLOps practices and deployment in cloud environments (AWS, GCP, or Azure). - Strong analytical and problem-solving skills with attention to detail. - Good communication and collaboration abilities. - Bachelors/Masters degree in Computer Science, Data Science, AI, or related field. At Miratech, you will benefit from the following: - **Culture of Relentless Performance**: Join a technology development team with a 99% project success rate and significant revenue growth. - **Work From Anywhere Culture**: Enjoy the flexibility of remote work. - **Growth Mindset**: Access professional development opportunities, certification programs, mentorship, and talent investment programs. - **Global Impact**: Collaborate on impactful projects for top global clients. - **Welcoming Multicultural Environment**: Thrive in an inclusive work environment with open communication and team-building events. - **Social Sustainability Values**: Contribute to sustainable business practices focused on IT education, community empowerment, fair operating practices, environmental sustainability, and gender equality.,

You are sought after to join our team as a Senior Data Engineer, bringing with you over 10 years of experience in data engineering or a similar role. Your expertise in snowflake, SSIS, and Python (including NumPy and Pandas) is crucial for this role. Additionally, you must have a strong command of SQL and be well-versed in working with any cloud environment such as AWS & Azure. Proficiency in modern BI tools or other ETL tools, in addition to SSIS, would be an advantage.,

In this exciting opportunity at Cogent Innovation Pvt Ltd, as an AI/ML Developer Fresher, you will be expected to bring fresh perspectives and innovative ideas to the table. **Key Responsibilities:** - Showcase academic/internship/project work in AI - Demonstrate strong foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning - Engage in hands-on experience with AI projects such as image recognition, NLP chatbot, recommendation systems, etc. - Utilize Python proficiency and experience with TensorFlow, PyTorch, Scikit-learn, OpenCV, or Hugging Face libraries - Handle data using Pandas, NumPy, etc. - Required knowledge of LangChain **Qualifications Required:** - Bachelors degree in Computer Science, Information Technology, Data Science, AI/ML, or related field - Proficiency in Python and experience with AI libraries - Exposure to data handling using Pandas, NumPy, etc. - Knowledge of LangChain,

As a Mid-Level Data Engineer at the company, you will play a crucial role in the team, focusing on data engineering to ensure the quality and reliability of databases. Your tasks will involve handling large datasets, crafting SQL queries, and collaborating closely with both the tech team and business users. You will primarily be responsible for data validation and sourcing, working closely with the Quant team to guarantee data accuracy and reliability. Your main focus will be on maintaining data quality, availability, and troubleshooting complex data systems. While math and statistics knowledge is not mandatory, a strong foundation in data engineering and programming is essential. - Collaborate with tech team and business users for data validation and sourcing - Work with large datasets and complex data systems - Write and debug SQL queries for data analysis - Ensure data quality, availability, and troubleshoot data issues - Collaborate with Quant team for accurate and reliable data Qualifications Required: - 5+ years of experience in data engineering or related field - Strong foundational knowledge of data engineering and relational databases, with expertise in MS SQL Server or Snowflake - Proficiency in writing SQL queries and debugging data issues - Knowledge of Python and relevant modules (Pandas, Requests, SQLAlchemy, Plotly, Matplotlib) - Familiarity with web development frameworks like Python Flask, Django, or Dash - Strong problem-solving skills and attention to detail - Computer science background preferred - Willingness to learn and adapt - Any familiarity with Capital IQ (CapIQ) would be a bonus In addition to the above responsibilities, you are expected to have a solid understanding of coding practices, including code repositories and deployment pipelines, or be open to learning them as part of your role.,

As a Senior Data Engineer at our company, your main role is to design, build, and maintain scalable data pipelines and architectures to support the Denials AI workflow. You will work under the guidance of the Team Lead, Data Management to ensure that the data is reliable, compliant with HIPAA, and optimized. **Key Responsibilities:** - Collaborate with the Team Lead and cross-functional teams to gather and refine data requirements for Denials AI solutions. - Design, implement, and optimize ETL/ELT pipelines using Python, Dagster, DBT, and AWS data services (Athena, Glue, SQS). - Develop and maintain data models in PostgreSQL; write efficient SQL for querying and performance tuning. - Monitor pipeline health and performance; troubleshoot data incidents and implement preventive measures. - Enforce data quality and governance standards, including HIPAA compliance for PHI handling. - Conduct code reviews, share best practices, and mentor junior data engineers. - Automate deployment and monitoring tasks using infrastructure-as-code and AWS CloudWatch metrics and alarms. - Document data workflows, schemas, and operational runbooks to support team knowledge transfer. **Qualifications:** - Bachelor's or Master's degree in Computer Science, Data Engineering, or related field. - 5+ years of hands-on experience building and operating production-grade data pipelines. - Solid experience with workflow orchestration tools (Dagster) and transformation frameworks (DBT) or other similar tools such as Microsoft SSIS, AWS Glue, Air Flow. - Strong SQL skills on PostgreSQL for data modeling and query optimization or any other similar technologies such as Microsoft SQL Server, Oracle, AWS RDS. - Working knowledge with AWS data services: Athena, Glue, SQS, SNS, IAM, and CloudWatch. - Basic proficiency in Python and Python data frameworks (Pandas, PySpark). - Experience with version control (GitHub) and CI/CD for data projects. - Familiarity with healthcare data standards and HIPAA compliance. - Excellent problem-solving skills, attention to detail, and ability to work independently. - Strong communication skills, with experience mentoring or leading small technical efforts. You will be working regular hours with on-call responsibilities for data pipeline incident response. The physical demands of the job include occasional movement within the work area, sitting, performing manual tasks, operating tools and office equipment, extending arms, kneeling, talking, and hearing. The mental demands require you to follow directions, collaborate with others, and handle stress. The work environment typically has minimal noise levels.,

As a Senior Data Analyst at Elsevier, you will be part of the Content and Data Analytics team under DataOps in Global Operations. Your primary focus will be on providing data analysis services using Databricks for product owners and data scientists of Elsevier's Research Data Platform, contributing to the development of leading data analytics products for scientific research, including Scopus and SciVal. - **Support data scientists within the Domains of the Research Data Platform by engaging in various analytical activities such as analyzing large datasets, performing data preparation, and reviewing data science algorithms. - Create advanced-level insights and recommendations, as well as lead analytics efforts with high complexity autonomously. - Possess a keen eye for detail, strong analytical skills, expertise in at least one data analysis system, curiosity, dedication to quality work, and an interest in scientific research. - **Minimum of 5 years of work experience. - Coding skills in at least one programming language (preferably Python) and SQL. - Familiarity with string manipulation functions like regular expressions. - Prior exposure to data analysis tools such as Pandas or Apache Spark/Databricks. - Knowledge of basic statistics relevant to data science. - Experience with visualization tools like Tableau/Power BI. Elsevier offers various benefits to promote a healthy work-life balance, including well-being initiatives, shared parental leave, study assistance, and sabbaticals. Additionally, the company provides comprehensive health insurance, flexible working arrangements, employee assistance programs, modern family benefits, various paid time off options, and subsidized meals. Elsevier prides itself on being a global leader in information and analytics, supporting science, research, health education, and interactive learning while addressing the world's challenges and fostering a sustainable future.,

Role Overview: As a Python Developer specializing in AI projects, you will be an integral part of our team in Tirunelveli. Your primary responsibility will be to design, develop, and deploy AI-based applications that address real-world challenges. Collaborating with diverse teams, you will utilize Python and related technologies to create scalable solutions. Key Responsibilities: - Develop and maintain Python-based AI models and algorithms for projects encompassing areas such as natural language processing (NLP), computer vision, predictive analytics, and automation. - Integrate AI frameworks like TensorFlow, PyTorch, or Scikit-learn into operational environments. - Optimize code to enhance performance, scalability, and efficiency in managing extensive datasets. - Work closely with data scientists, engineers, and stakeholders to convert business requirements into technical solutions. - Debug, test, and ensure the robustness of AI systems. - Stay abreast of the latest advancements in AI and Python development to drive innovation and enhance project outcomes. Qualification Required: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - Minimum of 3 years of hands-on experience as a Python Developer, with a strong focus on AI/ML projects. - Proficiency in Python programming, including libraries like NumPy, Pandas, Matplotlib, and AI-specific tools such as Keras and OpenCV. - Experience with version control systems like Git and cloud platforms such as AWS, Azure, or Google Cloud for AI deployments. - Familiarity with databases (SQL/NoSQL) and API development, including RESTful services using Flask or Django. - Excellent problem-solving abilities and the capacity to work autonomously or in a collaborative setting. Additional Company Details: The company is situated in Tirunelveli, Tamil Nadu, and prefers local candidates or individuals open to relocating to the area. The work environment follows a day shift schedule and requires in-person presence. Note: Preferred qualifications, benefits, and specific experience requirements have not been included as they are not explicitly specified in the provided job description.,

As an AI Developer at KritiLabs, you will be part of a dynamic team working on innovative projects that challenge conventional thinking. Your role will involve assisting in data analysis, supporting model development, conducting experiments, documenting processes, and collaborating with cross-functional teams to integrate AI/ML solutions into existing systems. Key Responsibilities: - Assist in collecting, cleaning, and analyzing data to uncover insights and prepare datasets for model training. - Support the design and implementation of machine learning models and algorithms under the guidance of senior team members. - Conduct experiments to evaluate model performance and contribute to the optimization of algorithms. - Help in documenting experiments, processes, and results to ensure clarity and reproducibility. - Work with cross-functional teams to integrate AI/ML solutions into existing systems and processes. - Engage in ongoing learning and development opportunities to enhance your understanding of AI/ML concepts and technologies. Qualifications: - Educational Background: Currently pursuing or recently completed a degree in Computer Science, Data Science, Mathematics, Statistics, or a related field. - Technical Skills: Familiarity with programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy). - Machine Learning Knowledge: Basic understanding of machine learning concepts and algorithms (e.g., regression, classification, clustering). - Analytical Skills: Strong problem-solving abilities with attention to detail and the ability to work with large datasets. - Communication: Good verbal and written communication skills, with the ability to articulate complex concepts clearly. - Team Player: Ability to work effectively in a collaborative team environment and take initiative in a fast-paced setting. - Projects or Coursework: Experience with AI/ML projects or relevant coursework is a plus. - Tools and Libraries: Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn is advantageous. Location: Chennai Experience: Fresher/Experienced Languages: English is mandatory, Other languages are an added advantage.,

Role Overview: As a Computer Vision Engineer at DeepQuanty Artificial Intelligence Labs, you will be part of a dynamic team in a startup environment. You will have the opportunity to leverage your experience in computer vision, machine learning, robotics, and control systems to tackle challenging product development tasks. This role offers high visibility within the company and the potential for increased responsibilities as you grow with us. Key Responsibilities: - Apply your cross-functional skill-sets, creativity, and experience to solve exciting product development challenges - Work with computer vision technologies to develop innovative solutions - Collaborate with team members to implement machine learning algorithms - Utilize frameworks like OpenCV, Tensorflow/Keras/PyTorch, Scikit-Learn, Matplotlib, Pandas, Numpy - Develop and maintain code in Python - Work on web frameworks such as Flask/Django/Tornado - Familiarity with development environments on Linux Qualifications Required: - 4+ years of experience as a software developer - Minimum 2 years of experience in AI/Machine Learning - Minimum 1 year of experience in Deep Learning - Bachelor's or Master's Degree in Computer Science or related field - Proficiency in Machine Learning in Computer Vision - Strong Python knowledge (Note: Additional details about the company were not provided in the job description.),

As a Lead AI Engineer at our company, you will be responsible for designing, developing, and deploying cutting-edge AI/ML solutions tailored for FCSD after-sales service operations. You will lead a team of AI engineers through the full lifecycle of AI product development. Your deep expertise in machine learning, strong programming skills, and passion for solving complex business problems will directly impact customer experience. **Key Responsibilities:** - **Technical Leadership:** - Lead and mentor a team of AI engineers, fostering collaboration and innovation. - Provide technical guidance throughout the AI solution development lifecycle. - Drive best practices in MLOps, model development, testing, and deployment. - Stay updated on the latest AI/ML advancements and recommend their application to business challenges. - **Hands-on AI Development:** - Design, build, and deploy end-to-end AI/ML models for after-sales service needs. - Develop scalable and production-ready code for AI applications. - Perform data exploration, model training, evaluation, and optimization. - Integrate AI solutions with existing enterprise systems and data pipelines. - **Strategy & Collaboration:** - Collaborate with product managers, data scientists, business stakeholders, and IT teams to deliver impactful AI solutions. - Translate complex business problems into well-defined AI/ML technical requirements and architectural designs. - **Problem Solving:** - Identify opportunities to enhance efficiency, reduce costs, and improve customer satisfaction in after-sales service using AI. - Debug and troubleshoot complex AI systems and data issues. **Qualification Required:** - Doctorate / Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, Data Science, or related field. - 5+ years of experience in Artificial Intelligence, Machine Learning, or Data Science roles. - 2+ years of experience leading a team of engineers or data scientists. - Proficiency in Python (TensorFlow, PyTorch, scikit-learn, pandas, numpy). - Experience in designing, building, and deploying machine learning models in production. - Understanding of machine learning algorithms, NLP techniques, and cloud platforms. - Knowledge of MLOps practices, causal inference, reinforcement learning, or optimization techniques. - Strong problem-solving skills and communication abilities. The preferred qualifications include familiarity with after-sales service operations, customer support systems, or automotive industry data, and contributions to open-source projects or personal AI/ML projects.,

Role Overview: As an AI Solution Developer, your primary responsibility will be to develop AI-based solutions to enhance the capabilities of the Cyber and Fraud Detection teams. You will collaborate with subject matter experts to adapt tools and improve them based on user feedback. Leveraging Python and associated libraries, you will build and deploy machine learning models and user interfaces. Key Responsibilities: - Develop and deploy AI-based solutions using Python. - Build user interfaces using Streamlit, Gradio, Flask, and other relevant frameworks. - Collaborate with subject matter experts to understand requirements and adapt tools accordingly. - Implement ETL (extract transform load) processes for data management and transformation. - Utilize libraries such as pandas and scikit-learn for data manipulation and machine learning tasks. - Continuously enhance tools based on user feedback and data insights. - Support the AI department in upskilling the Cyber and Fraud Detection teams. - Assist in integrating new AI tools and technologies. - Provide technical guidance and support to team members. Qualifications Required: - Proficiency in Python programming. - Knowledge of Large Language Models (LLMs) and machine learning. - Experience with Streamlit, Gradio, and Flask for building interfaces. - Understanding of the data lifecycle and ability to utilize user feedback for continuous improvement. - Knowledge of ETL processes. - Familiarity with pandas and scikit-learn libraries. - Strong collaboration and teamwork skills. - Attention to detail and rigor. - Adaptability and ability to manage change. - Excellent oral and written communication skills. (Note: No additional details about the company were provided in the job description.),

As a Senior Engineer Data Scientist specializing in AI & Machine Learning, your role will involve leading the entire lifecycle of machine learning projects, from data acquisition and feature engineering to model training, validation, deployment, and monitoring in a cloud environment. You will also be responsible for architecting and implementing advanced Generative AI solutions, developing and fine-tuning Large Language Models (LLMs), and building robust Retrieval-Augmented Generation (RAG) and Multi-Modal RAG pipelines. Additionally, you will design and implement evaluation frameworks to measure the performance, fairness, and safety of LLMs and other generative models, ensuring they meet high standards for reliability and accuracy. Your responsibilities will also include performing deep-dive data analysis using advanced statistical methods, developing autonomous and semi-autonomous AI agents, and leveraging Google Cloud Platform (GCP) services to build scalable AI/ML solutions. Clear communication of technical concepts and model results to both technical and non-technical audiences will also be a crucial aspect of your role. Key Responsibilities: - Lead end-to-end model development for machine learning projects - Architect and implement advanced Generative AI solutions - Design and implement evaluation frameworks for AI systems - Perform deep-dive data analysis using advanced statistical methods - Research and develop autonomous AI agents - Utilize Google Cloud Platform services for building AI/ML solutions - Communicate complex technical concepts effectively to various audiences Qualifications Required: - Bachelor's degree in Computer Science, Statistics, Engineering, Mathematics, or a related quantitative field - Six or more years of professional experience in data science, machine learning, or a related role - Expert-level proficiency in Python and its core data science libraries - Deep theoretical and practical knowledge of machine learning algorithms and deep learning - Hands-on experience in developing and deploying Generative AI solutions - Strong proficiency in SQL for data extraction and analysis - Experience with cloud computing platforms, specifically Google Cloud Platform If you have the following qualifications, it would be even better: - Master's or Ph.D. in a relevant quantitative field - Practical experience in developing AI agents using specific frameworks - Experience in designing and implementing robust LLM evaluation metrics - Experience with voice and speech technologies - Familiarity with MLOps/LLMOps principles and tools - GCP Professional Machine Learning Engineer certification Kindly note that the above-mentioned qualifications and requirements are essential for excelling in this role as a Senior Engineer Data Scientist in the field of AI & Machine Learning.,

As a Gen AI/ ML Data Scientist at Quadratyx, you will play a crucial role in developing machine learning models to support recommendation systems and NLP projects. Your insights will drive product and service optimization, contributing to better and faster decision-making for organizations worldwide. Here is a breakdown of your key responsibilities: - Develop machine learning models for recommendation systems and NLP projects - Provide actionable insights for product and service optimization - Build and maintain scalable ETL pipelines - Optimize data storage solutions (data lakes, columnar formats) - Ensure data accuracy for analytics - Analyze complex datasets to uncover trends and patterns - Generate and present insights that drive strategic decisions - Collaborate with product and service teams to understand data needs In this role, you will report to the Project Manager and will need to demonstrate proficiency in Python (Pandas, NumPy), SQL, Java, LLMs, Lang Chain, Generative AI technologies, ML frameworks (TensorFlow, PyTorch), and data engineering tools (Spark, Kafka). Your technical expertise, combined with strong data analysis skills, will allow you to present findings to both technical and non-technical stakeholders effectively. To qualify for this position, you should hold a Bachelor's Degree in Computer Science, Data Analytics, Engineering, or a related field and have 4 to 6 years of experience in data science and data engineering. Critical thinking abilities, autonomy, and excellent communication skills are essential for success in this role. Quadratyx is committed to being an equal opportunity employer, valuing diversity and inclusion. Interested candidates are encouraged to email their profiles to jobs@quadratyx.com for consideration.,

You will be a Data Scientist with 3-6 years of experience, specializing in classic machine learning models. Your role will involve GCP deployment, regression, classification, and casting mechanisms. You will be expected to have expertise in machine learning techniques such as classification, regression, computer vision, and neural networks. Additionally, your responsibilities will include utilizing algorithms like decision tree and boosting techniques. Your technical skills should encompass tools like TensorFlow, Keras, PyTorch, OpenCV, Seaborn, Numpy, Pandas, Selenium, SQL, Git/GitLab, Spark, JIRA, ScikitLearn, and optimization methods. - Apply scientific methods to analyze and solve software engineering problems - Develop and apply software engineering practices and knowledge in research, design, development, and maintenance - Exercise original thought and judgment while supervising the technical and administrative work of other software engineers - Build skills and expertise in software engineering discipline to meet standard expectations for the role - Collaborate effectively with other software engineers and stakeholders - 3-6 years of experience as a Data Scientist - Proficiency in classic machine learning models - Strong knowledge of GCP deployment, regression, classification, and casting mechanisms - Skills in business analysis, analytical thinking, problem-solving, decision-making, leadership, managerial, and time management - Expertise in machine learning techniques like classification, regression, computer vision, and neural networks - Familiarity with algorithms such as decision tree and boosting techniques - Technical proficiency in TensorFlow, Keras, PyTorch, OpenCV, Seaborn, Numpy, Pandas, Selenium, SQL, Git/GitLab, Spark, JIRA, and ScikitLearn - Experience with optimization methods including linear, quadratic, integer, convex, dynamic programming, quasi-Newton methods, and numerical methods - Database skills in MsSQL, Postgres, MsAccess, GCP, and Vertex AI The company works in the field of Software Engineering, focusing on the development, maintenance, and optimization of software solutions and applications. As a senior software engineer at Capgemini, you will lead the development of tools for Data Scientists and classic machine learning, cloud machine deployment, and casting mechanisms. You will also explore Python skills as part of your responsibilities, collaborating effectively with other team members and stakeholders.,

You will be part of a global team working across diverse business areas, brands, and geographies, aiming to deliver business outcomes and drive transformative impact on a global scale. Your main responsibilities will include designing and deploying end-to-end machine learning pipelines on cloud platforms like Azure and Snowflake, building efficient ETL pipelines for data preparation and model training, scaling machine learning infrastructure to handle large datasets, and implementing MLOps frameworks to automate model deployment and monitoring. Additionally, you will be involved in monitoring model drift, deploying machine learning models as REST APIs, establishing CI/CD pipelines, ensuring secure ML deployments, and developing modular and reusable ML packages. - Design and deploy end-to-end machine learning pipelines on cloud platforms to deliver scalable, production-ready solutions - Build efficient ETL pipelines to support data preparation, model training, and evaluation on modern platforms - Scale machine learning infrastructure to handle large datasets and enable real-time processing for critical applications - Implement MLOps frameworks to automate model deployment, monitoring, and retraining - Monitor and measure model drift to maintain ongoing model effectiveness - Deploy machine learning models as REST APIs using frameworks such as FastAPI, Bento ML, or Torch Serve - Establish robust CI/CD pipelines for machine learning workflows using tools like Git and Jenkins - Ensure secure ML deployments, addressing risks such as adversarial attacks and maintaining model integrity - Build modular and reusable ML packages using object-oriented programming principles - Develop clean, efficient, and production-ready code by translating complex business logic into software solutions - Continuously explore and evaluate MLOps tools, integrating best practices into the development process - Foster cross-functional collaboration by partnering with product teams, data engineers, and other stakeholders - Lead data labeling and preprocessing tasks to prepare high-quality datasets for training and evaluation - Stay updated on advancements in machine learning, cloud platforms, and secure deployment strategies to drive innovation in ML infrastructure - Master's degree in Computer Science, Computational Sciences, Data Science, Machine Learning, Statistics, Mathematics, or any quantitative field - Expertise with object-oriented programming languages such as Python and C++ - Strong proficiency in Python libraries like NumPy, Pandas, PyTorch, TensorFlow, and Scikit-learn - Proven experience in designing and deploying ML systems on cloud platforms like AWS, GCP, or Azure - Hands-on experience with MLOps frameworks, model deployment pipelines, and model monitoring tools - Track record of scaling machine learning solutions from prototype to production - Experience building scalable ML systems in fast-paced, collaborative environments - Working knowledge of adversarial machine learning techniques and their mitigation - Familiarity with Snowpark ML and Snowflake Cortex - Experience with Azure ML and Azure ML Studio,

As an experienced Data Scientist in Customer Success Analytics, your role will involve leading the design and development of predictive and prescriptive models to empower the Customer Success organization. You will focus on churn and upsell prediction, behavioral signal detection, and proactive intelligence to enhance engagement and retention within the account base. Your expertise in data science, business acumen, and automation mindset will be crucial in transforming large-scale Customer Success and product usage data into actionable insights. - Predictive & Prescriptive Analytics: - Develop and maintain churn prediction, upsell propensity, and engagement forecasting models using advanced statistical and machine learning techniques. - Create signal intelligence frameworks to identify early indicators of customer risk and opportunity. - Apply feature engineering, segmentation, and cohort analysis to enhance predictive accuracy. - Automation & Scalability: - Automate recurring analytics tasks, reports, and alert systems using Python, SQL, and workflow orchestration tools like Airflow and Power Automate. - Collaborate with Data Engineers to operationalize ML models and integrate outputs with CRM and analytics dashboards. - Proactive Intelligence & Benchmarking: - Design baseline and benchmarking frameworks across industries, revenue tiers, and client types. - Deliver proactive signals, trend detection, and alerts for retention and expansion opportunities. - Data Quality & Governance: - Define and enforce data validation rules to ensure sensible data checks and anomaly detection. - Evaluate data completeness and correctness, collaborating with Data Engineering to resolve pipeline or data quality issues. - Cross-Functional Collaboration: - Partner with Customer Success, Product, and Sales teams to embed data-driven recommendations into playbooks and engagement models. - Collaborate with BI and MIS teams to ensure model outputs are visible, actionable, and measurable in dashboards. As a qualified candidate for this role, you should possess: - Bachelor's/Master's degree in Data Science, Statistics, Computer Science, Applied Mathematics, or a related field. - 8-10 years of experience in applied data science, preferably in SaaS or B2B environments. - Hands-on expertise in Python (pandas, scikit-learn, NumPy, matplotlib, seaborn) and SQL. - Experience in predictive modeling, clustering, classification, and regression techniques. - Proficiency with BI and visualization tools (Power BI, Tableau) for integrating and communicating model outputs. - Familiarity with CRM data (HubSpot, Salesforce, Gainsight) and usage analytics. - Exposure to cloud data environments (AWS, Azure, GCP) and ML pipeline deployment preferred. - Strong communication skills with the ability to translate complex models into actionable business insights. In addition to technical qualifications, key competencies for this role include: - Predictive & Statistical Modeling - Machine Learning Implementation - Signal & Trend Intelligence Design - Data Quality & Governance - Cross-Functional Collaboration - Automation & Scalable Model Deployment - Storytelling with Data - Customer Success Metrics Expertise (NRR, GRR, Churn, Adoption, NPS) - Proactive, Problem-Solving Mindset Your main objectives in this role will be to: - Transition Customer Success from reactive insights to predictive intelligence. - Implement automated signal systems to identify churn or upsell opportunities before CSM intervention. - Maintain

You are a skilled Python Tech Lead with a strong interest in artificial intelligence and machine learning. As a Python/ML Tech Lead, your key responsibilities will include: - Proficiency in Python programming language. - Minimum 4+ years of hands-on experience in python and ML. - Strong background in machine learning algorithms and frameworks. - Understanding the requirements and objectives of the assigned projects. - Recommending appropriate approaches and technologies to deploy to achieve the objectives. - Iterating the development process to improve the effectiveness of the models. - Implementing parallel processing and other techniques to enhance processing speed. - Deep understanding of data extraction with Computer Vision and Deep learning libraries. - Excellent problem-solving and analytical skills. - Ability to understand project requirements and objectives, and translate them into actionable development tasks. - Effective communication with stakeholders to provide technical insights and project updates. - Ability to lead and mentor a team of developers, ensuring adherence to best practices and coding standards. - Strong project management skills, including task prioritization, resource planning, and risk management. Nice to have skills include experience with deep learning frameworks such as TensorFlow or PyTorch, familiarity with natural language processing (NLP) techniques, previous work on computer vision projects, and demonstrated experience and success in computer vision and text extraction projects. You will be working with Python, Python Flask, NLP (Content extraction), Pandas, OCR, Deep Learning, OpenCV, Tesseract, Computer Vision (Image Processing), TensorFlow, PyTorch, Keras, Scikit- learn, Paddle, ML, ML Algorithms, Neural Networks (CNN), Git, CI/CD, Cloud Experience (Any) to fulfill your responsibilities effectively.,