About the Role:Grade Level (for internal use):
10
S&P Global Corporate
The Role: Senior Data Scientist
Location: Princeton, NJ, New York, N, or Charlottesville, VA. Toronto, ON, Calgary, AB, Mexico City, MX, or London, UK (hybrid -2 days onsite per week)
The Team:
The Collection Platforms & AI team you will work on building ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global and our clients. You will spearhead development of production-ready AI products and pipelines while leading-by-example in a highly engaging work environment. You will work in a global team and encouraged for thoughtful risk-taking and self-initiative.
The Impact:
- The Collection Platforms & AI team has already delivered breakthrough products and significant business value over the last 5 years.
- In this role you will be developing our next generation of new products while enhancing existing ones aiming at solving high-impact business problems.
What’s in it for you:
- You will be part of a dynamic team that solves diverse problems using applied machine learning and web development with an end-to-end implementation of the solution: inception, prototyping, development, and productionizing.
- Be a part of a global company and build solutions at enterprise scale.
- Be a part of and grow with a highly skilled, hands-on technical team.
- Contribute to solving high-complexity, high-impact problems end-to-end.
- Build end-to-end production-ready pipelines from ideation to deployment.
Key Responsibilities
- Develop and deploy large-scale ML and GenAI-powered products and pipelines.
- Own all stages of the data science project lifecycle, including:
Develop, deploy, monitor, and scale models through the full Software Development Life Cycle into production (including both ML and GenAI services).
Perform exploratory data analysis, proof-of-concepts, model benchmarking, and validation experiments for both ML and GenAI approaches.
Partnering with business leaders, domain experts, and end-users to gather requirements and align on success metrics.
Follow coding standards, perform code reviews, and optimize data science workflows.
Evaluation, interpretation, and communication of results to executive stakeholders.
Technical Requirements:
- Strong grasp of statistics, probability, and the mathematics underpinning modern AI.
- Linear programming and optimization.
- Multi-dimensional optimizers, such as Adam, SGD, Gradient Descent 3
- Ability to adjust weights for full/partial tuning of LLMs.
- Hands-on experience with any large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval
- Intermediate to expert proficiency in Python (NumPy, Pandas, SpaCy, scikit-learn, PyTorch/TF 2, Hugging Face Transformers).
- Understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems.
- Solid understanding of database structures and SQL.
- Ability to perform independent research and synthesize current AI/ML research, with a track record of applying new methods in production.
- Experience in end-to-end GenAI or advanced NLP projects, such as NER, table extraction, OCR integrations, or GNN solutions.
- Familiarity with orchestration and deployment tools: Airflow, Redis, Flask/Django/FastAPI, SQL, R-Shiny/Dash/Streamlit.
- Openness to evaluate and adopt emerging technologies and programming languages as needed.
- Public contributions or demos on GitHub, Kaggle, StackOverflow, technical blogs, or publications.
- 5+ years in professional work within AI space or building statistical/mathematical quantitative models in production.
Preferred Qualification
- Advanced technical degree (Master and above) in any of Sciences, Technology, Engineering and Mathematics.
- Experience in productionizing AI applications.
- Experience with multi-modal LLMs and integrating vision and text for autonomous agents.
Right to work requirements for US based out Candidates:
This role is open only for candidates with indefinite right to work within the USA.
Compensation/Benefits Information (US Applicants Only):
S&P Global states that the anticipated base salary range for this position is $90,000 2 $160,000. Final base salary for this role will be based on the individuals geographical location as well as experience and qualifications for the role.
In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan.
This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please .
Right to work requirements for Canada based out candidates:
This role is open to candidates with indefinite right to work within Canada.
Compensation/Benefits Information: (This section is only applicable to Canadian Candidates:) S&P Global states that the anticipated range of compensation for this position is 95,000 CAD to 140,000 CAD. Final compensation for this role will be based on the individuals performance, geographic location, as well as experience level, skill set, training, licenses, and certifications. In accordance with Ontario's new regulations effective January 1, 2026, this job posting provides information on expected compensation. S&P Global will not be utilizing artificial intelligence in our hiring process. Additionally, we are committed to transparency and will inform all interviewed candidates of hiring decisions within 45 days of their interview. This posting is for an existing vacancy, and we encourage you to reach out for further information regarding our hiring practices or any questions you may have. Thank you for considering a career with us!
