The Prime Financial Services (PFS) QTR team’s mission is to develop and maintain sophisticated mathematical models, methodologies, and production infrastructure to help the Prime business thrive across cash, stock borrow/loan, and synthetic financing.
As a Vice President / Associate in PFS Quantitative Trading & Research team, you will work closely with PFS stakeholders (trading, technology, and risk) to identify opportunities to transform, automate, and optimize trading and risk/pricing workflows. The role covers both traditional prime inventory/collateral optimization and systematic trading and risk management, from research and prototyping through production deployment, monitoring, and performance analysis. Strong communication and ownership are critical, as you will regularly translate quantitative ideas into business impact and partner directly with senior desk stakeholders.
Job Responsibilities
- Partner with PFS desks to build data-driven analytics that automate and optimize risk, inventory, and financing decisions.
- Research and develop systematic strategies (signals, hedging, execution logic) supporting inventory trading, risk hedging, and client analytics.
- Build portfolio optimization frameworks for prime inventory, financing books, and hedging overlays (including constraints, transaction costs, and risk limits).
- Devise solutions for systematic book management and improved stability/usage of collateral and inventory.
- Contribute to the full lifecycle: idea generation, research, prototype, production implementation, controls, monitoring, and performance attribution.
- Perform scenario analysis, post-trade analysis, and investigations into model/algorithm behavior and historical performance.
- Build robust, maintainable quant libraries and pipelines integrated into the broader PFS ecosystem and tooling.
- Deliver quantitative insights that improve desk decision-making and operational efficiency.
- Maintain appropriate governance and control functionality for models and analytics in production.
**Required Qualifications, Capabilities and Skills **
- Advanced degree (Master’s/PhD or equivalent) in a quantitative discipline (Math, Stats, Physics, Engineering, Computer Science, or similar).
- Experience in quantitative modeling in equities or closely related asset classes.
- Strong understanding of statistics, financial mathematics, and optimization (linear/convex/conic optimization preferred).
- Familiarity with PFS products (stock loan/borrow, cash financing, synthetic financing) and related market microstructure.
- Demonstrated ability to work with large, complex, high-dimensional data and deliver production-quality analytics.
- Strong software engineering skills with proficiency in Python and capabilities in efficiently delivering solutions leveraging Generative AI models.
- Experience with research-to-production delivery, including testing, monitoring, and performance measurement.
- Ability to communicate complex quantitative concepts clearly to trading and senior stakeholders.
- Strong ownership mindset, drive, and ability to work in a front-office environment.
Preferred Qualifications, Capabilities and Skills
- Experience applying machine learning methods to trading, forecasting, or risk problems.
- Prior work on execution algorithms, transaction cost modeling, or alpha/risk signal research.
- Experience with portfolio construction under real-world constraints (limits, liquidity, costs, borrow/financing constraints).
- Knowledge of kdb+/q is preferred (or willingness to learn quickly).
- Knowledge of C++ is a plus.