Senior Data Scientist (AI/ML) in Bengaluru, India is listed on Jobeax. Browse 30,000+ vacancies available.
We are looking for a hands-on Data Scientist to join the Commodities At Sea (CAS) team. The role combines large-scale data processing, data wrangling and analytical problem-solving with the development of reliable, production-ready data products for maritime and commodity-flow analytics.
The successful candidate will work extensively with Python and PySpark, use R where appropriate, and collaborate with product managers, industry analysts, data scientists and technology partners. The role also contributes to cloud and DevOps activities across AWS, Docker and Terraform when needed.
A key part of this position is applying generative AI and intelligent workflow automation to improve how the team discovers, validates, transforms and operationalizes data. This includes building secure, observable and human-governed AI-assisted workflows, evaluating their quality, and integrating them responsibly into existing data pipelines and business processes.
Data Science, Engineering & Quality
Design, build and maintain scalable data-processing and analytical workflows using Python, PySpark and SQL; Collect, clean, reconcile and transform large, complex, disconnected and semi-structured datasets into analysis-ready and product-ready assets.
Develop reusable data components, features, models, validation checks and monitoring that improve the quality, reliability and explainability of CAS outputs.
Perform exploratory analysis and root-cause investigation to identify anomalies, answer business questions and recommend data or process improvements.
Build and optimize extraction, transformation and loading workflows using AWS data services and distributed-computing technologies.
Create fit-for-purpose analytical tools, prototypes and visualizations that help product, research and data-science stakeholders make informed decisions.
AI Workflow Automation
Identify high-value opportunities to automate repetitive data and research workflows using generative AI, machine learning and rules-based orchestration.
Design and implement AI-assisted workflows such as document and data extraction, semantic classification, summarization, entity matching, anomaly triage, metadata enrichment, code assistance and natural-language interfaces to curated data.
Build workflow components using large language model APIs, prompt templates, structured outputs, retrieval-augmented generation (RAG), tool/function calling and agentic patterns where appropriate.
Integrate AI components with data pipelines, APIs and business processes, with clear human review points for consequential or low-confidence outputs.
Create evaluation datasets and automated tests for accuracy, relevance, grounded ness, robustness, latency and cost; Apply responsible AI and security-by-design practices, including access control, data minimization, secrets management, auditability, traceability and protection against prompt injection or unintended data exposure.
Document AI workflow design, assumptions, limitations and operating procedures, and enable colleagues to use approved AI capabilities effectively.
Cloud, DevOps & Delivery
Package workloads in Docker containers and contribute to reproducible development and deployment practices.
Support AWS-based processing, storage, orchestration, monitoring and troubleshooting for analytical workloads.
Contribute to infrastructure-as-code using Terraform and to CI/CD practices for automated testing, scanning and deployment.
Work with stakeholders to define deliverables, manage dependencies and risks, and take ownership of quality and timely delivery.
Support production incidents and continuous improvement through structured troubleshooting, observability and root-cause analysis.
Develop a strong understanding of maritime shipping, commodity flows and their relationship with economic, market and policy developments.
Translate ambiguous business questions into clear analytical approaches, data requirements and measurable outcomes.
Communicate methods, findings, trade-offs and limitations clearly to technical and non-technical audiences.
3-6 years of relevant experience in data science, data engineering, analytics engineering or a closely related role, including at least 3 years of hands-on experience with Python and Spark/PySpark.
- Strong practical knowledge of Python data tooling and software-engineering fundamentals, including modular design, testing, version control and code review.
- Strong SQL skills and a successful track record of manipulating, processing and extracting value from large and heterogeneous datasets.
- Practical experience developing AI/ML or generative-AI solutions, including prompt design, structured outputs and systematic evaluation.
- Working knowledge of cloud platforms, preferably AWS, and familiarity with Docker-based development or deployment.
- Ability to independently structure problems, investigate root causes, balance quality with delivery, and collaborate in a multidisciplinary team.
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Informatics, Information Systems, Engineering, Artificial Intelligence, Machine Learning, or another quantitative discipline from a reputed institution.
Preferred / Beneficial Experience
Experience with R for statistical analysis or specialized analytical workflows.
Experience with retrieval-augmented generation, embedding/vector search, LLM orchestration frameworks, agentic workflows or model evaluation and observability.
Experience deploying secure AI applications in an enterprise environment, including integration with approved model platforms and internal data sources.
Experience with AWS services for data processing, storage, orchestration, serverless computing, monitoring or model/AI workloads.
Experience with Terraform, CI/CD pipelines, container security, vulnerability remediation and production support.
A proactive, self-directed approach with strong ownership of quality, documentation and delivery.
Sound judgment about when to use conventional automation, machine learning or generative AI, rather than applying AI by default.
Commitment to continuous learning in data, AI, cloud engineering and the maritime domain.
Reliable, maintainable and well-tested data and AI workflows that improve product quality and team efficiency.
Clear evidence that AI-assisted outputs are evaluated, monitored, secure and appropriately governed.
Faster conversion of complex data into trusted insights and scalable product capabilities.
Strong cross-functional partnerships and clear communication of assumptions, risks and outcomes.
Platts for news and pricing; S&P Global enables businesses, governments, and individuals with trusted data, expertise, and technology to make decisions with conviction. We are Advancing Essential Intelligence through world-leading benchmarks, data, and insights that customers need in order to plan confidently, act decisively, and thrive economically in a rapidly changing global landscape. Advancing Essential Intelligence.
We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us https://jobeax.com/link/rrgSbSNh31iOlqKr finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We're committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.
Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.
Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.
At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. Recruitment Fraud Alert
S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, 'pre-employment training' or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here.
S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. If you need an accommodation during the application process due to a disability, please send an email to: [HIDDEN TEXT] and your request will be forwarded to the appropriate person.