Vice President, Data Scientist

In this role, you’ll make an impact by:

• Supporting oversight of FX, interest rate, and credit derivatives pricing models and curve & volatility calibration used across the markets business.
• Monitoring model behavior through P&L analysis, valuation review, and risk monitoring to identify issues, trends, and control gaps.
• Preparing and supporting MRMG governance materials, model documentation, and regulatory submissions related to production models.
• Partnering with stakeholders across Markets, Risk, Quantitative Analytics, Technology, and Control functions to ensure robust model performance and governance.
• Applying data science and analytical techniques to improve model monitoring, exception detection, and control effectiveness.
• Contributing to the development of a unified semantic data layer to improve consistency, transparency, and usability of pricing, risk, and control data.
• Helping enable agentic and automated workflows that improve scalability, efficiency, and control execution.
• Delivering clear insights and reporting that enhance decision-making, execution quality, and operational effectiveness.
• Identifying opportunities to strengthen controls, improve data quality, and enhance end-to-end production model oversight.

To be successful in this role, we’re seeking the following:

• Bachelor’s degree or equivalent combination of education and experience required; advanced degree in Data Science, Statistics, Mathematics, Quantitative Finance, Financial Engineering, Computer Science, or a related field preferred.
• Significant experience in data science, quantitative analytics, model oversight, market risk, valuation controls, or a related discipline within financial services.
• Strong understanding of FX, interest rate, and credit derivatives, including pricing model concepts and associated risk measures.
• Experience with P&L monitoring, model performance assessment, valuation analysis, or risk monitoring in a markets environment.
• Knowledge of model governance frameworks, validation processes, MRMG engagement, and regulatory expectations.
• Strong technical skills in Python, C++, SWIG, SQL, and data analysis.
• Experience working with large and complex datasets, with the ability to improve data quality, structure, and usability.
• Strong analytical thinking, problem-solving capability, and the ability to communicate complex findings clearly to technical and non-technical stakeholders.
• Ability to work effectively across teams in a fast-paced, highly controlled environment.

• Master’s degree or PhD in a quantitative discipline.
• Experience supporting regulatory reviews, governance forums, or model committee processes.
• Familiarity with semantic data models, workflow automation, anomaly detection, or machine learning techniques.
• Exposure to strategic data initiatives within markets, risk, or controls organizations.