Senior Data Scientist

Seasoned Technical Recruiter | Building high-performing Teams | Searching for Innovative Minds | Talent Advisor | Mentor | Certified DEI Professional…

About The Role

Grade Level (for internal use): 10

Team Overview

Our Data and AI Engineering Team consists of skilled professionals focused on creating innovative and scalable data solutions. We specialise in cloud technologies, especially AWS and Snowflake, and prioritise data security and governance. Collaboration is key, as we work closely with Data Scientists and ML Engineers to advance impactful data projects. We encourage continuous learning and are actively adopting new technologies like Generative AI models and advanced machine learning tools to improve our data platforms and achieve outstanding outcomes.

Role Impact

In this role, you will design and implement scalable data architectures aligned with strategic goals, especially those supporting all stages of the Machine Learning (ML) and Generative AI (GenAI) lifecycle. You will apply your expertise in Snowflake, Python, and cloud technologies to maintain strong data security and integrity. Your work will drive innovation by developing, optimising, and maintaining production-level data pipelines that support both analytical and predictive modelling, enhancing data processing efficiency and enabling data-driven decision-making across the organisation.

Responsibilities

• ML Data Pipeline Development: Create and uphold scalable, reliable, and secure data infrastructure essential for Machine Learning model training, validation, and inference in production settings.
• Feature Store Collaboration: Partner with Data Scientists to design, build, and maintain a centralized Feature Store, ensuring consistency, reusability, and low-latency access to features for model training and deployment.
• GenAI Data Handling: Develop and execute data ingestion and processing workflows for text and unstructured data, including methods for vectorisation and populating vector databases to support Retrieval-Augmented Generation (RAG) architectures.
• Core Data Engineering: Build and maintain robust ELT/ETL processes within Snowflake and AWS to integrate diverse, large-scale data sources, ensuring excellent data governance, quality, and performance for general business intelligence.
• MLOps Partnership: Collaborate closely with ML Engineers to operationalise data flows to and from MLOps platforms (e.g., SageMaker, MLflow), focusing on automating pipelines and managing data versioning.
• Query and Compute Efficiency: Optimize data storage and computing resources across the platform to speed up data science experiments and model training workloads, while managing costs effectively.
• Data Security and Compliance: Implement advanced security measures to safeguard sensitive data used in AI datasets, maintaining data integrity and confidentiality in line with governance standards.

Required Skills And Experience

• Data Engineering Expertise (5+ Years): Extensive experience in a core Data Engineering role, including 5+ years working with Snowflake and strong skills in SQL and Python for data manipulation and engineering.
• Data Science Enablement: Demonstrated experience building and optimizing data pipelines specifically for Machine Learning model training and deployment (e.g., feature engineering, time-series data handling, complex schema management).
• Cloud Computing: Solid practical experience with AWS services (S3, Lambda, EC2, ECS) for creating reliable, scalable cloud data solutions.
• Distributed Processing: Familiarity with distributed computing frameworks such as PySpark or Dask for large-scale data transformation.
• Data Security: Strong knowledge of RBAC security models and secure data connection protocols.
• Communication: Excellent communication and teamwork skills, with a proven history of effective collaboration with Data Science and Business teams.

Preferred Qualifications

• MLOps / MLOps Platforms: Hands-on experience integrating data systems with MLOps platforms (e.g., MLflow, Amazon SageMaker) for production model deployment.
• Generative AI Data: Experience with vector databases (e.g., Pinecone, ChromaDB) and familiarity with data preparation for LLMs and RAG architectures.
• Feature Store Expertise: Practical or theoretical knowledge of Feature Stores (e.g., Feast, Tecton) and their role in the ML lifecycle.
• Advanced Data Orchestration: Experience with modern orchestrators like Apache Airflow, Prefect, or Dagster for managing complex, data-science-focused workflows.
• Experience with Cortex AI or comparable cloud AI tools.
• Certifications in Snowflake, AWS Data Analytics, or related areas.

What's In It For You

Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress.

Our People: We're more than 35,000 strong worldwide. Our team is driven by curiosity and a belief that Essential Intelligence can help build a more prosperous future for us all. We're committed to a more equitable future and to helping our customers find new, sustainable ways of doing business.

Our Values: Integrity, Discovery, Partnership. We focus on Powering Global Markets with integrity, discovery, and close collaboration with each other and our customers to achieve shared goals.

Benefits

We take care of you, so you can take care of business. We provide everything you—and your career—need to thrive at S&P Global.

• Health & Wellness: Health care coverage designed for the mind and body.
• Flexible Downtime: Generous time off to stay energized.
• Continuous Learning: Resources to grow your career and skills.
• Invest in Your Future: Competitive pay, retirement planning, education benefits with company-matched student loan contributions, and financial wellness programs.
• Family Friendly Perks: Benefits for partners and children.
• Beyond the Basics: Perks like retail discounts and referral incentives.

Equal Opportunity Employer: 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, please contact EEO.Compliance@spglobal.com.

For more information on benefits by country, visit: spgbenefits.com/benefit-summaries

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