Senior Data Scientist

Position Summary:

Senior Data Scientist with excellent hands-on technical skills responsible for designing and building end-to-end ML/AI solutions, implementing technical strategy, and mentoring engineering colleagues to build scalable production systems.

The Team:

The candidate will join a growing team of AI Engineers & Data Scientists as a member of the Data Science and Platforms team in Market Intelligence (MI) Enterprise Solutions (ES) at S&P Global. We work alongside product teams across MI ES on break-through ideas using tools and techniques spanning the entire spectrum of Data Science, Statistics, Machine Learning, Deep Learning, Gen AI, Operations Research, Data and Machine Learning Engineering. We are responsible for the end-to-end data science life cycle, right from ideation to developing Proof of concepts (PoC) and finally building and maintaining production data science/ML/AI applications/products/features.

The Impact:

• This is a great time to be joining a truly global team on a great technology journey. This is a great product covering multi-asset classes in both a pre/post-trade capacity with real-time insights.
• If you want to be an integral part of this forward-thinking team with a drive to succeed and the opportunity to enhance your development career and expand your technical skill sets, then this is the role for you.
• Your challenge will be reducing the time to market for products without compromising quality, by using innovation and technical skills.

Whats in it for you:

• Be a part of an industry leading, Fortune 500 company
• Be a part of GREAT PLACE TO WORK Certified firm
• Be a part of a People First organization that Values Partnership, Integrity, and Discovery to Accelerate Progress
• Develop and deliver industry-leading software solutions using cutting-edge technologies and the latest toolsets.
• Plenty of training and development programs that support continuous learning and skill enhancement.
• Build a fulfilling career with a truly global and leading provider of financial market intelligence, data, and analytics.

Responsibilities

• ML, Gen AI, NLP, LLM Model Development: Design and develop custom ML, Gen AI, NLP, LLM Models for batch and stream processing-based AI ML pipelines. Model components will include data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM model development, fine-tuning and prompt engineering and ensure the solution meets all technical and business requirements. Work closely with other members of data science, MLOps, technology teams in the design, development, and implementation of the ML model solutions.

• Internal Collaboration: Collaborate closely with product teams, business stakeholders, MLOps, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.

• Documentation: Write and maintain comprehensive documentation of ML modelling processes and procedures for reference and knowledge sharing.

• Develop Models Based on Standards and Best Practices: Ensure that the models are designed and developed while adhering to specified standards, governance and best practices in ML model development as specified by senior Data Science and MLOps leads.

• Assist in Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions.

Essential Skills

• 6+ years of professional hands-on experience leveraging large sets of structured and unstructured data to develop data-driven tactical and strategic analytics and insights using ML, RAG, and NLP.
• Capable of implementing machine learning techniques to tackle business challenges.
• Knowledgeable in statistical analysis and data visualization tools (such as Pandas, Matplotlib, and Seaborn) for analysing and presenting data insights.
• Solid understanding of statistics and machine learning techniques.
• Proficient in feature engineering methods to improve model performance.
• Experienced in A/B testing and experimental design to assess the effectiveness of models.
• Should be able to produce high-quality Python code suitable for production.
• Capable of integrating large language models (LLMs) or multimodal models into production systems.
• Familiar with various generative AI frameworks, including LangGraph and LangChain.
• Skilled in prompt engineering techniques to optimize the performance of generative AI models.
• Knowledgeable in fine-tuning LLMs and constructing retrieval-augmented generation (RAG) pipelines.
• Working knowledge of Agentic AI and MCP concepts.
• Proficient in Git-based workflows, including GitHub Actions, CI/CD, and version control.
• Expert-level Python programming skills with experience in ML frameworks (scikit-learn, TensorFlow/PyTorch)
• Good exposure with AWS services: Lambda, Step Functions, EC2, ECS Fargate, API Gateway, SQS, SNS, SageMaker, Bedrock, RDS,
• Advanced knowledge of data storage solutions: S3, DynamoDB, PostgreSQL
• Exposure in search and retrieval systems using OpenSearch/Elasticsearch
• Hands-on experience with LLMs, AWS Bedrock, OpenAI APIs, and Google Gemini models
• Expert knowledge of Docker containerization and AWS container orchestration
• Deep understanding of MLOps practices, model versioning, and deployment strategies
• Strong knowledge of software engineering best practices, Git workflows, and SDLC processes

People Skills

• Able to translate business problems into problems that can be solved with Data Science
• Able to communicate technical ideas effectively to non-technical audience
• Ability to work in a team which prioritizes collaboration & problem solving over rigid hierarchy
• Curious and open-minded attitude to new approaches
• Ability to accept feedback and adopt suggestions

Required Qualifications:

• Bachelor''s degree in Computer Science Engineering or related Engineering field/ Masters in Computer Applications

Preferred Qualifications:

• Masters or Ph.D degree in Computer Science, Mathematics or Statistics, Computational linguistics, Engineering, or a related field.