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data analyst, gsa data divisional office – gcoo Jobs in Mumbai

data analyst, gsa data divisional office – gcoo

data scientist

Tech Consulting

<div>
 
 About the Role:
 
 
 We are seeking an experienced and highly skilled Data Science Expert to join our growing team at our Mumbai office. This is a full-time, onsite role focused not only on solving complex data problems but also on mentoring and training Junior Data Science Engineers. The ideal candidate will bring deep technical expertise in data science and machine learning, along with a passion for teaching and developing talent.
 
 
 ________________________________________
 
 
 Key Responsibilities:
 
 
 &bull; Lead the development of end-to-end data science solutions using advanced ML, NLP, and Computer Vision techniques.
 
 
 &bull; Train, mentor, and support junior data science engineers in coding, model development, and best practices.
 
 
 &bull; Architect and implement AI-driven solutions such as chatbots, OCR systems, and facial recognition applications.
 
 
 &bull; Translate complex business problems into actionable data science projects and deliver measurable results.
 
 
 &bull; Design and lead internal workshops, code reviews, and learning sessions to upskill the team.
 
 
 &bull; Collaborate with engineering and product teams to deploy models and insights into production environments.
 
 
 &bull; Stay abreast of the latest AI/ML trends and integrate cutting-edge techniques into projects where applicable.
 
 
 ________________________________________
 
 
 Desired Skills &amp; Qualifications:
 
 
 &bull; Experience: 6+ years in Data Science/Machine Learning with at least 1&ndash;2 years of team mentoring or leadership experience.
 
 
 &bull; Education: Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, Statistics, or a related field.
 
 
 ________________________________________
 
 
 Technical Expertise Required:
 
 
 &bull; Strong proficiency in Python and SQL; R is a plus.
 
 
 &bull; Solid hands-on experience with Deep Learning and Neural Networks, particularly in Natural Language Processing (NLP), Generative AI, and Computer Vision.
 
 
 &bull; Familiarity with frameworks and libraries such as TensorFlow, Keras, PyTorch, OpenCV, SpaCy, NLTK, BERT, ELMo, etc.
 
 
 &bull; Experience developing Chatbots, OCR, and Face Recognition systems is preferred.
 
 
 &bull; Hands-on knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform).
 
 
 &bull; Experience applying statistical and data mining techniques such as GLM, regression, clustering, random forests, boosting, decision trees, etc.
 
 
 &bull; Strong understanding of model validation, performance tuning, and deployment strategies.
 
 
 ________________________________________
 
 
 
 
 
 Soft Skills:
 
 
 &bull; Excellent communication and presentation skills, especially in explaining complex models to non-technical audiences.
 
 
 &bull; Demonstrated ability to mentor, train, and lead junior team members effectively.
 
 
 &bull; Strong analytical and problem-solving mindset with a detail-oriented approach.
 
 
 ________________________________________
 
 
 What We Offer:
 
 
 &bull; Competitive salary and benefits
 
 
 &bull; A collaborative and intellectually stimulating environment
 
 
 &bull; Career growth and leadership development opportunities within a fast-paced team
 
</div>

Data Scientist

Kotak Mutual Fund

<div>
 
 
 Location:
 
 Kotak Mutual Fund
 
 
 
 Department:
 
 Data Science &amp; Analytics
 
 
 
 Reports To:
 
 Lead- Analytics
 
 
 
 
 
 
 Job Summary:
 
 
 
 We are looking for a forward-thinking and impact-driven
 
 Senior Data Scientist
 
 to lead the development of advanced analytics solutions that directly enhance the
 
 productivity and profitability
 
 of our
 
 Digital Business, Marketing, and Operations
 
 functions using data science and analytics.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 
 AI/ML Development:
 
 </li>
 <li>
 Design, develop, and deploy machine learning models including LLMs, predictive analytics, and fault detection systems using Python, Scikit-learn, XGBoost, and other frameworks. Also, manage the GenAI solutions using LLMs, LangChain for operational and business efficiency.
 </li>
 <li>
 
 Data Integration &amp; Visualization:
 
 </li>
 <li>
 Build and maintain interactive dashboards using Power BI, integrating data from SQL and AWS.
 </li>
 <li>
 
 Project Management:
 
 </li>
 <li>
 Lead cross-functional projects, manage timelines, and ensure successful delivery of analytics solutions. Experience with tools like JIRA and Bitbucket is a plus.
 </li>
 <li>
 
 Business Impact:
 
 </li>
 <li>
 Collaborate with stakeholders to identify opportunities, define KPIs, and deliver data-driven insights that enhance decision-making and operational efficiency.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer/data science or related field (Master&rsquo;s preferred).
 </li>
 <li>
 3+ years of experience in data science, machine learning, and analytics.
 </li>
 <li>
 Strong programming skills in Python, Pyspark, SQL, and AWS analytics services.
 </li>
 <li>
 Experience with LLMs, LangChain is a plus
 </li>
 <li>
 Proficiency in Power BI, Power Platform, and automation tools.
 </li>
 </ul>
</div>

Senior Data Scientist

<div>
 
 Introduction
 
 
 
 A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio, including Software and Red Hat.Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in groundbreaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment
 
 
 
 Role Overview
 
 
 
 
 Your role and responsibilities
 
 
 
 We are seeking a Machine Learning Data Scientist with hands-on experience in building, training, and deploying ML models that solve real-world business problems. The ideal candidate should be proficient in ML algorithms, feature engineering, model evaluation, and deployment, with strong programming and statistical skills.
 
 
 
 Preferred Education
 
 
 
 Bachelor's Degree
 
 
 
 Mandatory Skills
 
 
 
 
 Required technical and professional expertise
 
 
 
 <ul>
 <li>
 Strong proficiency in Python for ML.
 </li>
 <li>
 Good understanding of statistics, probability, and hypothesis testing.
 </li>
 <li>
 Experience with ML frameworks (Scikit-learn, TensorFlow, PyTorch).
 </li>
 <li>
 Hands-on with data wrangling, feature engineering, and preprocessing.
 </li>
 <li>
 Practical experience with at least one cloud ML platform (Azure ML, AWS SageMaker, or GCP Vertex AI).
 </li>
 <li>
 Experience with model deployment and lifecycle management (MLflow or similar).
 
 
 </li>
 </ul>
 
 Preferred Technical And Professional Experience
 
 
 
 Good to Have:
 
 
 <ul>
 <li>
 Experience with NLP (transformers, embeddings) or Computer Vision (CNNs).
 </li>
 <li>
 Exposure to Databricks MLflow &amp; Feature Store.
 </li>
 <li>
 Familiarity with big data frameworks (Spark, Databricks, Hadoop).
 </li>
 <li>
 Experience with real-time ML inference pipelines.
 </li>
 </ul>
</div>

Data Scientist-Artificial Intelligence

BNP Paribas

<div>
 
 About BNP Paribas Group
 
 
 
 
 BNP Paribas is a top-ranking bank in Europe with an international profile. It operates in 71 countries and has almost 199 000 employees
 
 . The Group ranks highly in its three core areas of activity: Domestic Markets and International Financial Services (whose retail banking networks and financial services are grouped together under Retail Banking &amp; Services) and Corporate &amp; Institutional Banking, centred on corporate and institutional clients. The Group helps all of its clients (retail, associations, businesses, SMEs, large corporates and institutional) to implement their projects by providing them with services in financing, investment, savings and protection. In its Corporate &amp; Institutional Banking and International Financial Services activities, BNP Paribas enjoys leading positions in Europe, a strong presence in the Americas and has a solid and fast-growing network in the Asia/Pacific region.
 
 
 
 About BNP Paribas India Solutions
 
 
 
 Established in 2005, BNP Paribas India Solutions is a wholly owned subsidiary of BNP Paribas SA, a leading bank in Europe with an international reach. With delivery centers located in Bengaluru, Chennai and Mumbai, we are a 24x7 global delivery center. India Solutions services three business lines: Corporate and Institutional Banking, Investment Solutions and Retail Banking for BNP Paribas across the Group. Driving innovation and growth, we are harnessing the potential of over 6000 employees, to provide support and develop best-in-class solutions.
 
 
 
 About Business Line/Function
 
 
 
 GM Data &amp; AI Lab leverages the power of Machine Learning and Deep learning to drive innovation in various business lines. Our primary goal is to harness the potential of vast amounts of structured and unstructured data to improve our services and provide value. Today we are a team of around 40+ Data Scientists based in Paris, London, Frankfurt, Lisbon, New York, Singapore and Mumbai.
 
 
 
 Job Title
 
 
 
 Data Scientist (Quant Research)
 
 
 
 Date
 
 
 
 Department:
 
 
 Front Office Support
 
 
 Location:
 
 
 Mumbai
 
 
 
 Business Line / Function
 
 
 
 Global Markets &ndash; Data &amp; AI Lab
 
 
 
 Reports To
 
 
 
 (Direct)
 
 
 
 Grade
 
 
 
 (if applicable)
 
 
 (Functional)
 
 
 
 Number Of Direct Reports
 
 
 
 NA
 
 
 
 Directorship / Registration
 
 
 
 NA
 
 
 Position Purpose
 
 
 Your work will center on designing and deploying AI solutions for time series forecasting, financial modeling, anomaly detection and other Quant related usecases. We use AI to discover patterns, classify information, and predict likelihoods. Our team works on building, refining, testing, and deploying these models to support various business use cases, ultimately driving business value and innovation.
 
 
 As a Data Scientist on our team, you can expect to work on challenging projects, collaborate with stakeholders to identify business problems, and have the opportunity to learn and grow with our team. A typical day may involve working on model development, meeting with stakeholders to discuss project requirements/updates, and brainstorming/debugging with colleagues on various technical aspects.
 
 
 At the Lab, we're passionate about staying at the forefront of AI research, bridging the gap between research &amp; industry to drive innovation and to make a real impact on our businesses.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Develop and maintain AI models on time series &amp; financial date for predictive modelling, including data collection, analysis, feature engineering, model development, evaluation, backtesting and monitoring.
 </li>
 <li>
 Identify areas for model improvement through independent research and analysis, and develop recommendations for updates and enhancements.
 </li>
 <li>
 Working with expert colleagues, Quant and business representatives to examine the results and keep models grounded in reality.
 </li>
 <li>
 Documenting each step of the development and informing decision makers by presenting them options and results.
 </li>
 <li>
 Ensure the integrity and security of data.
 </li>
 <li>
 Provide support for production models delivered by the Mumbai team but potentially as well for other models to any of the Asian/EU/US time zones.
 
 
 </li>
 </ul>
 Technical &amp; Behavioral Competencies
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in a numeric subject with understanding of economics and markets (eg.: Economics with a speciality in Econometrics, Finance, Computer Science, Applied Maths, Engineering, Physics)
 </li>
 <li>
 Knowledge of key concepts in Statistics and Mathematics such as Statistical methods for Machine learning, Probability Theory and Linear Algebra.
 </li>
 <li>
 Knowledge of Monte Carlo Simulations, Bayesian modelling &amp; Causal Inference.
 </li>
 <li>
 Experience with Machine Learning &amp; Deep Learning concepts including data representations, neural network architectures, custom loss functions.
 </li>
 <li>
 Proven track record of building AI models on time-series &amp; financial data.
 </li>
 <li>
 Programming skills in Python and knowledge of common numerical and machine-learning packages (like NumPy, scikit-learn, pandas, PyTorch, PyMC, statsmodels).
 </li>
 <li>
 Ability to write clear and concise code in python.
 </li>
 <li>
 Intellectually curious and willing to learn challenging concepts daily.
 
 
 </li>
 </ul>
 
 Skills Referential
 
 
 
 Behavioural Skills:
 
 
 Ability to collaborate / Teamwork
 
 
 Critical thinking
 
 
 Communication skills - oral &amp; written
 
 
 Attention to detail / rigor
 
 
 
 Transversal Skills
 
 
 
 Analytical Ability
 
 
 
 Education Level
 
 
 
 Bachelor Degree or equivalent
 
 
 Experience Level
 
 
 At least 2 years
</div>

Data Scientist (Quant Research) - GM Data & AI Lab

Siddharth Carbochem Products Limited

<div>
 Founding Applied Research Scientist (PhD) &mdash; Industrial Intelligence Platform
 
 Location: Mumbai (preferable) | Type: Full-time |
 
 
 WHO THIS IS FOR
 
 PhD (or final-year PhD) in AI/ML/CS (or related) who wants their work running on real production lines. You care about solid theory, and you care even more about measurable impact on uptime, yield, and energy.
 
 
 WHY THIS ROLE
 
 &bull; Own the 0&rarr;1 research agenda for edge inference, time-series modeling, and control&mdash;and see it in production quickly
 
 &bull; Work directly with founders and pilot customers across chemicals, pharma, food, steel, and energy
 
 &bull; Early equity with real upside, plus the autonomy to choose methods and tooling to hit performance targets
 
 
 WHAT YOU&rsquo;LL DO
 
 &bull; Take ideas from paper to plant: ingest &rarr; features &rarr; inference &rarr; control loop &rarr; monitoring/rollback
 
 &bull; Design models for non-stationary, multivariate sensor data; quantify uncertainty and detect drift
 
 &bull; Optimize for edge and latency (quantization, distillation, pruning, ONNX/TensorRT, streaming inference)
 
 &bull; Define datasets, metrics, and SLOs; build evaluation harnesses and ablations that stick
 
 &bull; Partner with controls/process engineers to integrate models with existing systems
 
 
 WHAT WE&rsquo;RE LOOKING FOR
 
 &bull; PhD in AI/ML/CS (or closely related); strong publications or equivalent applied work
 
 &bull; Depth in one or more: time-series/state-space models, anomaly detection, predictive maintenance, Bayesian/UQ, RL/MPC for control, physics-informed ML
 
 &bull; Solid software fundamentals: Python/C++, PyTorch/JAX, containers, CI/CD, observability
 
 &bull; Experience with streaming systems and edge deployment is a plus (ONNX, TensorRT, gRPC)
 
 &bull; Bonus: industrial protocols (OPC UA, Modbus, MQTT), MLOps, model compression/compilers
 
 
 WHAT YOU&rsquo;LL GET
 
 &bull; equity, competitive base, and performance incentives with a clear formula
 
 &bull; Real ownership of a product area (edge inference and applied research roadmap)
 
 &bull; Day-one production impact with access to pilot environments and decision-makers
</div>

Al/ml phd

Tata Consultancy Services

<div>
 
 
 TCS is Hiring
 
 -Clinical Safety Scientist
 
 
 
 location
 
 - Mumbai, Noida, Bengaluru
 
 
 
 Experience Range
 
 - 5 to 10
 
 
 Preferred Educational Qualification for the role -
 
 Any life science
 
 
 Graduate
 
 
 
 
 
 Job Description
 
 
 
 
 
 Literature Review
 
 
 
 Literature review to assess ICSR, new safety signal, for inclusion in Aggregate report, for inclusion in DSR (Drug Safety reports).
 
 
 Provide MAH comments for selected literature
 
 
 Review of Literature Strategy
 
 
 Design and interpretation of various types of studies in medicine, levels of evidence, study power for the purpose of safety analyses.
 
 
 Thesaurus used for indexing medical scientific literature, relevant for literature search strategy tailoring (both ad-hoc and systematic).
 
 
 Review and interpretation of current expert therapeutic guidelines for the purpose of various safety analyses.
 
 
 Review of outputs triaged by the safety scientist for scientific accuracy taking into consideration all of the above criteria
 
 
 
 Aggregate Reports:
 
 
 
 Authoring Safety Sections of SSSRs, DSUR, aCO &amp; PBRER.
 
 
 Authoring of RMP updates &amp; implementation plans.
 
 
 Provides methodology (in collaboration with Roche clinical safety) for data presentation and assessment in the pertinent safety sections of the aggregate report (use outside the indication scope, use in special population, medication errors, characterization of risks etc.)
 
 
 Asses the new information received on important safety concerns for the medicinal product.
 
 
 Reviews the content prepared by the Safety Scientist for medical, regulatory and scientific accuracy
 
 
 
 Signal Management
 
 
 
 Review of various types of listings for Signal Detection
 
 
 Understanding of signal journey and knowledge of signal management systems and process requirements.
 
 
 Perform Signal validation with a brief summary.
 
 
 DSR - Complete authoring, Single case analysis &amp; MAH comments, Drafting Overall Conclusion and Review
 
 
 Tailoring strategy and methodology for signal assessment
 
 
 Overall assessment of the signal based on the presented data and respective recommendation for action
 
 
 Reviews the content prepared by the Safety Scientist for medical, regulatory and scientific accuracy
 
 
 
</div>

Clinical Scientist

Cipla

<div>
 
 
 PURPOSE OF THE ROLE
 
 
 
 To lead the development and implementation of data-driven strategies to enhance procurement, planning, third-party manufacturing, and distribution processes. This role aims to leverage advanced analytics and Artificial Intelligence / Machine Learning to optimize operations, drive efficiencies, and support Cipla&rsquo;s commitment to delivering high-quality healthcare solutions.
 
 
 
 
 
 
 KEY RESPONSIBILITIES
 
 
 
 
 
 
 
 Data Strategy Development for Procurement and Planning and Distribution
 
 
 <ul>
 <li>
 Develop and execute a comprehensive Supply Chain data science and AI strategy to optimize supply chain operations that aligns with procurement and planning and distribution objectives, focusing on service levels and cost to serve models
 </li>
 <li>
 Identify and integrate key data sources (internal and external) to enhance visibility and accuracy in procurement decisions and planning &amp; distribution processes.
 </li>
 <li>
 Evaluate and implement emerging technologies and tools (e.g., GenAI, IoT, digital twins) that enhance data collection, analysis, and visualization capabilities.
 </li>
 <li>
 Collaborate with procurement and planning and distribution teams to prioritize data science initiatives that drive operational efficiencies and cost savings.
 </li>
 </ul>
 
 
 
 
 
 Advanced Analytics and Modeling for Supply Chain Optimization
 
 
 <ul>
 <li>
 Lead the initiative to deploy scientific (based on secondary stock and sales data) replenishment strategies in Trade (India and Global markets)
 </li>
 <li>
 Design and implement predictive AI/ML models to enhance demand forecasting accuracy, optimize inventory levels, distribution planning and improve supplier performance evaluation.
 </li>
 <li>
 Drive innovation by exploring and implementing advanced analytics techniques, machine learning models, and AI algorithms to derive insights and create value from large, complex datasets.
 </li>
 <li>
 Utilize machine learning algorithms to analyze historical data and identify trends that inform procurement strategies and planning cycles.
 </li>
 <li>
 Develop advanced analytics solutions to assess the performance of third-party manufacturers and optimize distribution logistics.
 </li>
 </ul>
 
 
 
 
 
 Collaboration and Stakeholder Engagement Across Functions
 
 
 <ul>
 <li>
 Work closely with cross-functional teams, including procurement, supply chain, planning, and IT, to identify data needs and ensure alignment on data initiatives.
 </li>
 <li>
 Support initiatives like Control Towers, Predictive Analytics, and Agentic Process Automation (APA) in alignment with GSCM&rsquo;s roadmap.
 </li>
 <li>
 Facilitate workshops and training sessions to educate stakeholders on data science methodologies and the value of data-driven decision-making in procurement and supply chain operations.
 </li>
 <li>
 Act as a liaison between data science team and business units to ensure that data solutions meet operational requirements and enhance overall performance.
 </li>
 <li>
 Communicate findings, recommendations, and project updates to senior management and key stakeholders as and when required.
 </li>
 </ul>
 
 
 
 
 
 Master Data Governance and Quality Assurance
 
 
 <ul>
 <li>
 Develop and implement master data governance frameworks to ensure data integrity, quality, and security across all data science initiatives related to procurement, planning, and distribution.
 </li>
 <li>
 Design and oversee data quality checks and validation processes to maintain high standards of data accuracy and reliability in analytics outputs.
 </li>
 <li>
 Ensure that all data science and AI initiatives comply with industry regulations, data privacy laws, and internal policies to safeguard sensitive procurement and supply chain information.
 </li>
 <li>
 Develop strategies to protect sensitive data and ensure compliance with data protection regulations, including monitoring and responding to potential data breaches.
 </li>
 <li>
 Ensure robust documentation, model governance, and audit-readiness of all analytics solutions.
 </li>
 </ul>
 
 
 
 
 
 Team Leadership and Development in Data Science
 
 
 <ul>
 <li>
 Lead and mentor a team of data scientists and analysts, machine learning engineers and AI experts fostering a culture of innovation, collaboration, and continuous learning focused on procurement and supply chain challenges.
 </li>
 <li>
 Set clear performance expectations and provide regular feedback to team members to support their professional development in data science applications.
 </li>
 <li>
 Encourage knowledge sharing and best practices within the team to enhance overall capabilities and effectiveness in addressing procurement and supply chain needs.
 </li>
 <li>
 Work closely with the SCM Academy to build data literacy and analytics capability across the function.
 </li>
 </ul>
 
 Represent the function in external forums, awards, and academic collaborations.
 
 
 
 
 
 
 Performance Measurement and Reporting for Continuous Improvement
 
 
 <ul>
 <li>
 Develop key performance indicators (KPIs) to measure the impact of data science initiatives on procurement, planning, third-party manufacturing, and distribution performance.
 </li>
 <li>
 Regularly report on the progress of analytical projects and their outcomes to senior leadership and stakeholders, highlighting successes and areas for improvement.
 </li>
 <li>
 Conduct post-implementation reviews to assess the effectiveness of data-driven solutions and identify opportunities for further optimization in supply chain processes.
 </li>
 </ul>
 
 
 
 
 
 Stake holder Management
 
 
 <ul>
 <li>
 Internal - Global Head of Digital Transformation and Operational Excellence, Procurement Team, Supply Chain Management Team, Planning Team, Finance Team, IT and Data Engineering Teams, Cipla Leadership Group
 </li>
 <li>
 External - Third-party manufacturers and suppliers, Stockists, Logistics service providers, Data analytics vendors and consultants, Regulatory bodies
 </li>
 </ul>
 
 
 
 
 
 ROLE PROFILE REQUIREMENTS
 
 
 
 
 Education
 
 
 
 Master&rsquo;s degree or PhD in Data Science, Statistics, Engineering, Computer Science, or a related field
 
 
 
 Experience
 
 
 
 12-15 years of experience in data science, analytics, or related fields, with a focus on procurement, planning, third-party manufacturing, or distribution and proven experience in leading digital transformation and AI/ML deployment at scale in the pharmaceutical or healthcare industry.
 
 
 
 
 
 
 Functional / Behavioral Skills required to execute the role
 
 
 
 TECHNICAL / FUNCTIONAL COMPETENCIES
 
 
 
 
 <ul>
 <li>
 Proficiency in data science tools, data warehouses and programming languages (e.g., Python, R, SQL, Agentic AI (MCP), AWS, Azure etc.).
 </li>
 <li>
 Experience with machine learning algorithms, statistical modeling, and data visualization tools (e.g., Tableau, Power BI, Gen AI).
 </li>
 </ul>
 
 
 
 
 BEHAVIORAL COMPETENCIES
 
 <ul>
 <li>
 Strong understanding of supply chain processes, procurement strategies, and planning methodologies.
 </li>
 <li>
 Excellent leadership and team management skills.
 </li>
 <li>
 Strong analytical and problem-solving abilities.
 </li>
 <li>
 Effective communication and interpersonal skills, with the ability to influence stakeholders at all levels.
 </li>
 <li>
 Strategic thinking and a results-oriented mindset.
 </li>
 </ul>
 
 
</div>

Lead – Supply Chain Digital transformation & Analytics

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