S&P Global Logo

S&P Global

Data Scientist

Posted Yesterday
Be an Early Applicant
In-Office
New York, NY, USA
90K-150K Annually
Senior level
In-Office
New York, NY, USA
90K-150K Annually
Senior level
Build and optimize AI/ML data pipelines, model metadata and lineage systems, feature engineering workflows, model monitoring, and AI governance infrastructure. The role uses Databricks, Spark, MLflow, knowledge graphs, and real-time pipelines to support model lifecycle management, data quality, agent discovery, and AI compliance. It also requires collaboration with data scientists and ML engineers, documentation of AI data architectures, and implementation of security controls for training data and model artifacts.
The summary above was generated by AI
About the Role:

Grade Level (for internal use):

10

S&P Global Corporate

AI Data Engineer

Location: NYC: 55 water street, two days per week onsite.


Role Overview

The AI Data Engineer will specialize in building and optimizing machine learning data pipelines, focusing on AI model tracking, lifecycle management, and integration with AI governance systems. This role combines data engineering expertise with AI/ML knowledge to support the organization's broader data and AI infrastructure initiatives.


Key Responsibilities

  • Design and implement specialized data pipelines for AI model metadata, training data lineage, and model performance metrics tracking.
  • Build data infrastructure on Databricks leveraging Spark for large-scale distributed dataset processing.
  • Develop MCP servers and enable AI data distribution via MCP.
  • Develop feature engineering pipelines and data preprocessing workflows for AI model training and inference.
  • Implement model versioning, experiment tracking, and model registry integration using MLflow or similar tools.
  • Create automated workflows for AI agent discovery, classification, and inventory management across the enterprise.
  • Design and maintain knowledge graph structures for representing AI model relationships, dependencies, and data lineage.
  • Build real-time data pipelines for AI model monitoring, drift detection, and performance tracking.
  • Develop data quality frameworks specific to AI training datasets and validation data.
  • Collaborate with data scientists to optimize data access patterns and feature store implementations.
  • Implement security and compliance controls for sensitive AI training data and model artifacts.
  • Create comprehensive documentation for AI data architectures, schemas, and integration patterns.

Required Skills and Qualifications


  • 5+ years of hands-on experience in data engineering, with at least 2 years focused on AI/ML workloads.
  • Expert proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
  • Strong experience with Databricks, Apache Spark, and distributed computing for ML workflows.
  • Deep understanding of the machine learning lifecycle, including model training, deployment, and monitoring processes.
  • Experience with feature engineering, data preprocessing techniques, and ML data pipelines.
  • Knowledge of vector databases, embeddings, and similarity search for AI applications.
  • Proficiency in SQL for structured and unstructured data management.
  • Understanding of data governance, model governance, and AI ethics principles.
  • Strong analytical and problem-solving capabilities with attention to data quality.
  • Excellent collaboration skills for working with data scientists, ML engineers, and architects.
  • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field.

Preferred/Nice-to-Have Skills

  • Experience with generative AI applications, including RAG (Retrieval-Augmented Generation) and fine-tuning.
  • Knowledge of LangChain, HuggingFace, or other GenAI frameworks.
  • Familiarity with Azure ML, AWS SageMaker, or Google Vertex AI platforms.
  • Experience with graph databases (Neo4j, Amazon Neptune) for knowledge graph implementation.
  • Understanding of AI model explainability and interpretability techniques.
  • Experience with A/B testing frameworks for ML model evaluation.
  • Certification in Databricks, AWS, Azure, or GCP AI/ML services.
  • Publications or contributions to open-source ML projects

NOTE: As part of the process there is a mandatory in person technical evaluation.


Right to work requirements for US based out candidates:

This role is open only for candidates with indefinite right to work within the US. 


Compensation/Benefits Information (US Applicants Only):
S&P Global states that the anticipated base salary range for this position is $90,000 USD – $150,000 USD. Final base salary for this role will be based on the individual’s geographical location as well as experience and qualifications for the role.

In addition to base compensation, this role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here.

What’s In It For You?

Our Mission:

Advancing Essential Intelligence.

Our People:

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 all.From 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 are changing the way people see things and empowering them to make an impact on the world we live in. 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.

Our Values:
Integrity, Discovery, Partnership

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.
Benefits:

We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global.
Our benefits include: 

  • Health & Wellness: Health care coverage designed for the mind and body.

  • Flexible Downtime: Generous time off helps keep you energized for your time on.

  • Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.

  • 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.

  • Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.

  • Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

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

Global Hiring and Opportunity at S&P Global:

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. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.

Recruitment Fraud Alert:

If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to [email protected]. 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.

-----------------------------------------------------------

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.  Only electronic job submissions will be considered for employment.  

 

If you need an accommodation during the application process due to a disability, please send an email to: [email protected] and your request will be forwarded to the appropriate person.  
 
US Candidates Only: Know Your Rights: Workplace discrimination is illegal

-----------------------------------------------------------

20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.1 - Middle Professional Tier I (EEO Job Group), SWP Priority – Ratings - (Strategic Workforce Planning)
HQ

S&P Global New York, New York, USA Office

55 Water Street, New York, NY, United States, 10041

S&P Global Hightstown, New Jersey, USA Office

Hightstown, United States

S&P Global Trenton, New Jersey, USA Office

Trenton, United States

Similar Jobs

2 Days Ago
Hybrid
New York, NY, USA
245K-335K Annually
Expert/Leader
245K-335K Annually
Expert/Leader
Fintech • Machine Learning • Payments • Software • Financial Services
Leads data science and machine learning initiatives for a global payment network. Partners with data scientists, software engineers, and product managers to develop scalable models and AI tools for fraud, risk, merchant acceptance, intelligence, and monitoring. Oversees model design, training, evaluation, validation, and implementation while translating technical insights into business outcomes and developing team talent.
Top Skills: SparkAWSCondaH2OMachine LearningPythonRRelational DatabasesScala
2 Days Ago
Hybrid
New York, NY, USA
Senior level
Senior level
Financial Services
Build measurement frameworks, KPI reporting, datasets, analyses, and predictive models for small business lending products. Partner with product, strategy, risk, finance, technology, and operations stakeholders to translate ambiguous business questions into actionable insights. Deliver executive-ready recommendations, benchmarking, customer behavior analyses, and performance reporting while maintaining data quality, governance, documentation, and auditability. Apply AI-assisted analytics responsibly in a regulated environment.
Top Skills: AIAWSOraclePythonRSnowflakeSQLTeradata
3 Days Ago
Hybrid
2 Locations
Senior level
Senior level
Financial Services
Leads customer and marketing analytics from business-question definition through data preparation, experimentation, reporting, and insight generation. Partners with finance, product, marketing, and business stakeholders to optimize campaigns, analyze customer journeys, measure program value, and support strategic decisions. Uses Python, SQL, cloud data platforms, web analytics, visualization, and advanced analytical methods to translate complex findings into actionable recommendations.
Top Skills: Adobe InsightAdobe SitecatalystAWSDatabricksHqlPythonSnowflakeSparksqlSQLTableau

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account