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.
Preferred Qualifications:
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.