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Data Scientist

Pay
USD 90,000–150,000/year · BaseAnnual period assumed. Location-specific pay — pay source
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.
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

Before you apply

Work authorization
Must already have the right to work in the USThis role is open only for candidates with indefinite right to work within the US

What you’ll work on

Full posting

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

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.

  • 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.

From the employer’s posting
Location: NYC: 55 water street, two days per week onsite.
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.
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.
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.

Benefits in the posting

Full benefits wording
  • Our benefits include:
  • Health & Wellness: Health care coverage designed for the mind and body.
  • 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.
  • Global Hiring and Opportunity at S&P Global:
  • Recruitment Fraud Alert:
  • -----------------------------------------------------------

From the employer’s posting.

About S&P Global

We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective.

In the employer’s words · Read in context

Apply at S&P Global

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 14, 2026today
Recorded sightings
1

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$195K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,828 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 8 and day 60.

At S&P Global, jobs usually come down by about day 18.

From 11,873 similar postings that came down, and 136 of S&P Global’s. Coming down is not always a hire.

S&P Global is hiring

28 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
  • 4% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • Databricks
  • GCP
  • MLflow
  • Neo4j
  • SageMaker
  • Spark
  • Hugging Face
  • PyTorch
  • scikit-learn
  • TensorFlow
Where the posting names them
- 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.
- 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.
- 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.
- 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
- 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.
- 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.
- 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.
- 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 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.

Your next step

Complete your application on spgi.wd5.myworkdayjobs.com. The employer’s form will show what is required.

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Already applied? Track this application

Has S&P Global posted this job before?

Yes. We’ve followed one other Data Scientist job there since April 2026. It came down after 7 days.

  1. New YorkCame down after 7 days, first seen Apr 27
  2. This jobUp 1 day so far, first seen Nov 14

About S&P Global

People
About 44,500 in 2025, up 5% from the year before.Annual report (SEC Form 10-K)
Company
Listed as SPGI.

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 1,403, the most 2,949, and the latest week had 2,098.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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 reportfraud@spglobal.com. 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.

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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: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person.  
 
US Candidates Only: Know Your Rights: Workplace discrimination is illegal

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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)
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Pay
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.
Location & working pattern

New York, NY

Working pattern and location restrictions need checking in the full posting.

Work authorization
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):

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