Job description

Primary Function: The Solutions Investment & Research Team (“IRT”) manages the investment due diligence, governance, operational due diligence, and research analytics and data intelligence efforts for Wealth Management discretionary and advisory assets. The Investment & Research Team comprises individuals in New York, London, and India and is highly collaborative across teams and regions. As a Vice President Quantitative Researcher in the Investment & Research Team, you will contribute to the design, development, and delivery of risk analytics and models, with a primary focus on collateral risk and lending value methodology. You will be expected to develop a deep understanding of the lending business, collateral functions, applicable regulations and policies. In this role, you will partner across different functions (Investment Solutions, Credit operations, Risk, Lending, Technology and model risk management) to deliver executive-quality insights that inform product and business strategy. Responsibilities: • Design, develop, and enhance quantitative models and analytics for lending value estimations, including frameworks that translate collateral characteristics into lending value and risk measures. • Perform empirical research to identify key risk drivers (market, liquidity, volatility, concentration, idiosyncratic risk) and incorporate them into model design. • Establish model performance benchmarks and accuracy measures. • Build deep domain expertise in the lending business, including collateral operations, margining workflows, and how collateral valuation impacts credit decisions and P&L. • Support product strategy by evaluating trade-offs (risk appetite vs. client competitiveness vs. operational feasibility) and quantifying impacts of methodology changes. • Partner with Technology and data teams to source, reconcile, and curate data Qualifications: • Advanced degree (PhD, MSc, or equivalent) in Mathematics, Physics, Statistics, Computer Science, or a related quantitative field. • 7+ years of quant experience and deep understanding of probability theory, risk/VaR and model assumptions/limitations. • Strong preference for candidate with background and experience in margin, lending and knowledge of financial products including equity, fixed income, commodity, HF, Private Investment, currency, and derivatives. • Preference for candidate with knowledge of wealth management businesses as well as risk, controls, and compliance. • Good coding skills in python • Good communication skills with the ability to clearly explain and defend domain concepts, methodologies, assumptions, and results to regulators and senior management, translating complex technical content into concise, decision-ready narratives. • Highly effective at multi-tasking and adapting to changing priorities in a dynamic business environment, and at continually assessing and reprioritizing focus on key priorities in delivering for the business Partner across different functions (Investment Solutions, Credit operations, Risk, Lending, Technology and model risk management) to deliver executive-quality insights that inform product and business strategy.

Requirements

Must-haves

Design, develop, and enhance quantitative models and analytics for lending value estimations, including frameworks that translate collateral characteristics into lending value and risk measures.
Perform empirical research to identify key risk drivers (market, liquidity, volatility, concentration, idiosyncratic risk) and incorporate them into model design.
Establish model performance benchmarks and accuracy measures.
Build deep domain expertise in the lending business, including collateral operations, margining workflows, and how collateral valuation impacts credit decisions and P&L.
Support product strategy by evaluating trade-offs (risk appetite vs. client competitiveness vs. operational feasibility) and quantifying impacts of methodology changes.
Partner with Technology and data teams to source, reconcile, and curate data
Advanced degree (PhD, MSc, or equivalent) in Mathematics, Physics, Statistics, Computer Science, or a related quantitative field.
7+ years of quant experience and deep understanding of probability theory, risk/VaR and model assumptions/limitations.
Strong preference for candidate with background and experience in margin, lending and knowledge of financial products including equity, fixed income, commodity, HF, Private Investment, currency, and derivatives.
Preference for candidate with knowledge of wealth management businesses as well as risk, controls, and compliance.
Good coding skills in python
Highly effective at multi-tasking and adapting to changing priorities in a dynamic business environment, and at continually assessing and reprioritizing focus on key priorities in delivering for the business
Partner across different functions (Investment Solutions, Credit operations, Risk, Lending, Technology and model risk management) to deliver executive-quality insights that inform product and business strategy.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

python

Platform: oracle-cloud
Effort: medium