About the Role:
Grade Level (for internal use):
09
The Team
S&P Global's Financial Risk Analytics team delivers state-of-the-art risk management solutions to financial institutions worldwide — from the world's largest tier-one banks to specialist niche firms. Our technology stack combines a fully vectorised pricing library with machine learning and big data capabilities, enabling precision at scale across counterparty credit risk, market risk, regulatory capital, and derivative valuation.
Responsibilities and Impact
As Sr Specialist, Quantitative Modeling, you will play a hands-on role in keeping our risk analytics platform running at its best — supporting clients, strengthening data integrity, and contributing to the evolution of our product. Your day-to-day impact will span operations, analytics, and development:
Operate and support Risk as a Service (RaaS) and Deployed Solutions, ensuring seamless daily performance and an exceptional experience for institutional clients across the globe.
Conduct data analysis across S&P Global's data estate and the Financial Risk Analytics Risk Factor Utility — managing data quality to maintain accurate, reliable inputs across our end-to-end workflow.
Investigate and resolve system, data, and process issues — diagnosing root causes and implementing proactive measures to prevent recurrence before they impact client-facing solutions.
Contribute to feature development by assisting in the implementation, testing, and documentation of new platform capabilities, gathering stakeholder requirements and providing structured feedback for continuous improvement.
Collaborate with cross-functional teams globally to resolve operational challenges, support client deliverables, and contribute to initiatives that strengthen product quality and analytical infrastructure.
Support client-facing outputs by ensuring the accuracy and integrity of risk factor data and model results delivered to institutional counterparties.
What We're Looking For
Basic Required Qualification s
Bachelor's degree in Mathematics, Statistics, Computer Science, Engineering, Finance, or a related quantitative discipline
Proficiency in Python or at least one other programming language (e.g., R, C++) applied to data analysis, quantitative modelling, or workflow automation
Demonstrable knowledge of financial risk concepts, including at least one of: counterparty credit risk, market risk, regulatory capital, or derivative valuation
Strong written and verbal communication skills, with the ability to convey technical findings clearly to both specialist and non-specialist audiences
Availability and willingness to work occasional evenings and/or weekends to support client deadlines and global time-zone requirements
Additional Preferred Qualification s
Experience supporting production systems or risk analytics platforms within a financial services or fintech environment
Practical experience with big data technologies or machine learning frameworks in a quantitative context
Knowledge of regulatory risk capital frameworks (e.g., Basel III/IV, FRTB, SA-CCR)
Experience in data quality management and end-to-end workflow validation within financial data pipelines
Proficiency in SQL or similar data querying languages for large dataset interrogation and manipulation
Exposure to derivative pricing models or risk factor simulation methodologies
Additional Information
Employees are required to work from the office a minimum of two days per week.
We require all candidates who reach the final stage of our interview process to attend at least one in-person interview, which is ordinarily at your nearest S&P Global office. This must be completed before we can proceed to an offer.
About S&P Global Market Intelligence
At S&P Global Market Intelligence, a division of S&P Global we understand the importance of accurate, deep and insightful information. Our team of experts delivers unrivaled insights and leading data and technology solutions, partnering with…