Associate, Portfolio Analytics | PGIM Strategic Capital Group (Hybrid / Newark, NJ)
About The Position
PGIM’s Strategic Capital Group (SCG) is responsible for providing institutional clients with asset-liability management, portfolio strategy, and asset allocation solutions harnessing PGIM’s multi-asset expertise across public and private credit. SCG oversees liability-aware portfolio construction and strategic asset design on behalf of its clients, while also partnering with other teams including PGIM Credit and PGIM Real Estate to deliver best-in-class private origination, credit underwriting, investment research, and risk management capabilities across a full range of asset classes. SCG is the investment manager for Prismic, a reinsurance platform launched by Prudential together with other strategic investors. This position is within the Portfolio Analytics team of SCG and will assume key responsibilities in the growth of our state-of-the-art quant platform for dynamic portfolio optimization based on rigorous asset-liability simulation and economic scenario generation. You will focus, in particular, on modeling the dynamics of diverse asset classes as well as underlying economic risk factors, which will feed into real portfolio construction projects, both for live deals and in-force business, not just post-allocation diagnostics. You will be based in our Newark, NJ office and will follow a hybrid schedule (3 days in-office).
Requirements
- Economics or Finance Ph.D., advanced degree from a quantitative finance program, or comparable academic experience within a quantitative discipline
- Solid programming background, including Python (pandas, numpy, scipy) and exposure to modern transformer technology and foundation models
- Reliable knowledge of core quant finance topics: probability theory, statistics, stochastic models, options theory, yield curve construction, fixed income analytics, CAPM, etc.—both at the technical level but also conceptually, in terms of basic financial intuitions accessible to non-quants
Nice To Haves
- Familiarity with structured products, private credit, real estate debt, and private equity, as well as previous exposure to insurance liabilities and asset-liability management concepts
- Knowledge about the theoretical foundations of quant finance and about macroeconomic frameworks
- Creativity, intellectual curiosity, and the ability to break down quantitative ideas for non-quant audiences
Responsibilities
- Build stochastic models to enhance and extend our proprietary real-world economic scenario generator
- Contribute to macro-factor and asset-level models that set key parameters within the scenario generator
- Develop advanced techniques to analyze emerging asset classes with sparse historical data
- Develop methodology and tools for attributing changes in asset-liability metrics to underlying risk factors
- Investigate and apply the latest quantitative and AI-based methods to concrete investment-strategy problems
- Work with teams across PGIM to properly model investment strategies across a range of public, private, and structured asset classes for use within our asset-liability simulations
Benefits
- Market competitive base salaries, with a yearly bonus potential at every level.
- Medical, dental, vision, life insurance, disability insurance, Paid Time Off (PTO), and leave of absences, such as parental and military leave.
- 401(k) plan with company match (up to 4%).
- Company-funded pension plan.
- Wellness Programs including up to $1,600 a year for reimbursement of items purchased to support personal wellbeing needs.
- Work/Life Resources to help support topics such as parenting, housing, senior care, finances, pets, legal matters, education, emotional and mental health, and career development.
- Education Benefit to help finance traditional college enrollment toward obtaining an approved degree and many accredited certificate programs.
- Employee Stock Purchase Plan: Shares can be purchased at 85% of the lower of two prices (Beginning or End of the purchase period).
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
