Private Bank, Solutions Investment Quantitative Research team, Vice President

JPMorgan Chase & Co. • New York, NY

16h

About The Position

Join JPMorgan’s Private Bank Solutions Investment Quantitative Research team as
a Vice President specializing in Fixed Income and Derivatives Risk Modeling and
Analytics. You'll work on challenging problems spanning factor modeling, risk
analytics, liquidity analysis, portfolio construction, and stress testing for
fixed income securities. The team works closely with portfolio managers, risk,
and lending teams across JPMorgan Wealth Management, as well as partnering with
Technology teams to deliver solutions at scale. The quantitative research team
is based in New York and Mumbai.

You will be responsible for researching and implementing quantitative models for
fixed income risk and P&L analytics to enhance our modeling capabilities and
expand coverage across the entire fixed income universe. You will serve as
a subject matter expert across all fixed income asset classes, including Government bonds, Investment Grade/High Yield corporates, Municipals, Securitized Products, Structured Products, Fixed Income Derivatives (swaps, swaptions, CDS), and Emerging Market Debt.

Requirements

• 7 years of direct experience as a model researcher and developer, preferably in a multi-asset class asset management environment with subject matter expertise in risk modeling and analytics within the fixed income and derivatives space
• Deep expertise in fixed income analytics (duration, convexity, OAS, spreads), credit modeling (DTS, hazard rates, default/recovery), securitized products (MBS/ABS/CMBS), and derivatives (swaps, CDS, swaptions)
• Solid understanding of investment models and tools including factor modeling, stress scenario analysis, performance attribution, portfolio construction, and optimization
• Ability to translate complex quantitative findings into actionable insights for portfolio managers and risk stakeholders
• Working knowledge of data vendors including MSCI, Bloomberg, Morningstar, FactSet, Markit, etc.
• Strong proficiency in Python with experience in data analysis libraries (pandas, NumPy), visualization tools (matplotlib, seaborn), and statistical modeling
• Advanced degree in quantitative discipline (PhD preferred) in Mathematics, Statistics, Financial Engineering, Economics, or related quantitative field

Responsibilities

• Factor Modeling: Design multi-factor risk models across all fixed income instruments
• P&L Attribution: Build frameworks isolating contributions from rates, spreads, convexity, basis risk, and currency
• Risk Analytics: Construct factors and covariances, develop instrument-specific risk models, build tracking error and volatility forecasting frameworks
• Stress Testing: Design frameworks for rate shocks, spread widening, liquidity crises, and historical events; develop scenario methodologies with tail risk and non-linear effects
• Research: Conduct empirical research, develop new factors, enhance models as markets evolve
• Validation & Governance: Conduct rigorous backtesting, validate assumptions, ensure comprehensive model documentation
• Technology & Data: Partner with Technology to productionize scalable models, build APIs, curate multi-vendor data
• Team work/leadership: Work closely with colleagues in NY and Mumbai. Provide direction to junior colleagues.

Benefits

• We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location.
• Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.
• We also offer a range of benefits and programs to meet employee needs, based on eligibility.
• These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree