Asks for

The ad says“Hands-on experience using cloud platforms (such as AWS, Azure, or GCP) for machine learning experimentation, training at scale, and model deployment.”
The ad says“Hands-on experience using cloud platforms (such as AWS, Azure, or GCP) for machine learning experimentation, training at scale, and model deployment.”
The ad says“Proven experience in computer vision techniques and applications, such as image/video processing, feature extraction, object detection, segmentation, and representation learning.”
The ad says“5+ years of hands-on programming experience, primarily in Python, with a strong focus on building, training, and evaluating machine learning and deep learning models.”
The ad says“Hands-on experience using cloud platforms (such as AWS, Azure, or GCP) for machine learning experimentation, training at scale, and model deployment.”
The ad says“Familiarity with version control systems (e.g., Git) and best practices for collaborative ML development.”
The ad says“Strong experience working with machine learning frameworks and libraries (e.g., PyTorch, TensorFlow, Keras, scikit-learn), including designing and implementing neural network architectures.”
The ad says“5+ years of hands-on programming experience, primarily in Python, with a strong focus on building, training, and evaluating machine learning and deep learning models.”
The ad says“Working knowledge of data storage and querying technologies (SQL and/or NoSQL) to support analytical and ML workflows.”
The ad says“5+ years of hands-on programming experience, primarily in Python, with a strong focus on building, training, and evaluating machine learning and deep learning models.”
The ad says“Strong experience working with machine learning frameworks and libraries (e.g., PyTorch, TensorFlow, Keras, scikit-learn), including designing and implementing neural network architectures.”
The ad says“Strong experience working with machine learning frameworks and libraries (e.g., PyTorch, TensorFlow, Keras, scikit-learn), including designing and implementing neural network architectures.”
The ad says“Working knowledge of data storage and querying technologies (SQL and/or NoSQL) to support analytical and ML workflows.”
The ad says“Strong experience working with machine learning frameworks and libraries (e.g., PyTorch, TensorFlow, Keras, scikit-learn), including designing and implementing neural network architectures.”

About the Role:

Grade Level (for internal use):

Job Description

About the Role :

S&P Global is seeking a Data Scientist III (Grade 10) to join our Data Science & Modeling team. In this hybrid role, you will help build and optimize the data infrastructure that powers analytics and machine learning across the organization. You’ll work closely with colleagues from data science, engineering, and business teams to deliver scalable, reliable, and cloud-enabled data solutions.

We welcome applicants from diverse backgrounds and encourage you to apply even if your experience doesn’t match every requirement.

What's in for you:

Impactful Work: You’ll play a key role in shaping the data infrastructure that powers advanced analytics and machine learning solutions across S&P Global. Your contributions will directly influence business decisions and product innovation.
Collaboration & Growth: Work alongside talented colleagues from data science, engineering, and business teams. You’ll have opportunities to learn, share knowledge, and grow your expertise in both data science and data engineering.
Cloud & Modern Tech: Gain hands-on experience with leading cloud platforms (such as AWS) and modern data tools, helping you stay at the forefront of industry trends.
Hybrid Flexibility: Enjoy a flexible work environment that supports both onsite collaboration and remote work, promoting work-life balance and productivity.
Inclusive Culture: Be part of a diverse and inclusive team that values different perspectives and backgrounds. We support your success and well-being, including accommodations during the hiring process.

Responsibilities:

Collaborate with stakeholders (data scientists, analysts, engineers, business teams) to understand data needs and translate them into actionable technical requirements.
Design, build, and maintain scalable data pipelines using modern tools and cloud platforms (such as AWS, Azure, or GCP).
Develop and maintain data infrastructure for analytics and machine learning, leveraging cloud-native technologies and services.
Improve data quality, lineage, and reliability, and troubleshoot issues across the data lifecycle.
Support the deployment and monitoring of analytics and ML solutions in production, working closely with data science and engineering peers.
Contribute to an Agile team environment, including documentation, code reviews, and iterative delivery.

Requirements:

University degree in Computer Science, Engineering, Mathematics, or a related discipline (or equivalent practical experience).
5+ years of hands-on programming experience, primarily in Python, with a strong focus on building, training, and evaluating machine learning and deep learning models.
Strong experience working with machine learning frameworks and libraries (e.g., PyTorch, TensorFlow, Keras, scikit-learn), including designing and implementing neural network architectures.
Proven experience in computer vision techniques and applications, such as image/video processing, feature extraction, object detection, segmentation, and representation learning.
Experience developing end-to-end ML workflows, from data preparation and feature engineering through model training, validation, and deployment, with an emphasis on model performance, robustness, and maintainability.
Working knowledge of data storage and querying technologies (SQL and/or NoSQL) to support analytical and ML workflows.
Hands-on experience using cloud platforms (such as AWS, Azure, or GCP) for machine learning experimentation, training at scale, and model deployment.
Familiarity with distributed and accelerated computing concepts relevant to ML workloads (e.g., multi-GPU training, distributed training, or large-scale inference).
Experience collaborating closely with data engineers and platform teams to integrate models into production pipelines, while maintaining ownership of model logic and performance.
Exposure to workflow orchestration or experiment management tools (e.g., Airflow, MLflow, or similar) for reproducible ML pipelines is a plus.
Familiarity with version control systems (e.g., Git) and best practices for collaborative ML development.
Strong ability to communicate results, trade-offs, and limitations of ML models clearly to both technical and non-technical stakeholders.

Nice to Have

Experience with data governance practices (privacy, security, access controls, compliance expectations).
Experience improving data observability (monitoring, alerting, SLAs, incident response).

Why This Role Matters

Your work will help teams across S&P Global use trusted, well-modeled, and well-delivered data to build analytics and ML capabilities—supporting product innovation and decision-making with robust data foundations.

About S&P Global Energy
At S&P Global Energy, our comprehensive view of global energy and commodities markets enables our customers to make superior decisions and create long-term, sustainable value. Our four core capabilities are: Platts for news and pricing; CERA for research and advisory; Horizons for energy expansion and sustainability solutions; and Events for industry collaboration.

S&P Global Energy is a division of S&P Global (NYSE: SPGI). 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. Learn more at www.spglobal.com/energy.

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)