Equity Finance Quantitative Strategist VP/SVP

Equity Finance Quantitative Strategist — VP/SVP

Join a high-impact, entrepreneurial quant team embedded directly within the Equity Finance trading desk. You will own the full lifecycle of quantitative models — from research and prototyping through production deployment — that directly drive P&L, optimize financial resource consumption, and give our clients a differentiated analytical edge. You will own the full quantitative model suite across equity swaps, securities lending, custom baskets, and prime brokerage — spanning liquidity management (ALM/MLO), valuation, counterparty risk, client analytics, factor-driven portfolio solutions, and hard-to-borrow pricing/locates.

Unlike large-bank quant factories, this role offers direct partnership with senior traders, visibility to desk leadership, and the autonomy to shape the analytical direction of a rapidly growing business. You will work directly with clients on bespoke portfolio solutions and build systems that traders use every day to make real-time decisions.

You will be part of a Global Quant team spanning New York and London, collaborating closely to ensure alignment on strategy, shared tooling, and state-of-the-art quantitative capabilities across regions.

What You Will Own

Quantitative Modelling & Analytics

• Design and implement pre-trade optimization models for funding, liquidity risk, and tenor mismatch — driving measurable P&L improvement
• Build factor analytics engines, custom basket construction tools, and risk decomposition frameworks for equity swap and securities finance portfolios
• Develop forward funding rate projection models and collateral optimization algorithms
• Create P&L attribution, risk factor analysis, and scenario modelling across Equity Swaps and Securities Finance
• Liquidity Modelling.

Client-Facing Analytics & Custom Solutions

• Partner directly with hedge fund and institutional clients to design and optimize custom basket strategies — portfolio construction, factor tilts, and rebalancing logic
• Develop bespoke quantitative tools that help clients analyze their portfolio exposures, optimize execution, and manage risk
• Serve as a technical counterpart to clients on complex structured and systematic strategies, translating their investment objectives into quantitative implementations
• Build analytics that surface client flow patterns, profitability drivers, and resource consumption (balance sheet, capital, funding) at a granular level

AI, Machine Learning & Intelligent Automation

• Apply machine learning techniques (gradient boosting, NLP, clustering) to identify patterns in client flow, predict funding demand, and optimize inventory positioning
• Leverage large language models (LLMs) and generative AI to automate research workflows, extract insights from unstructured data, and build intelligent decision-support tools for the trading desk
• Develop AI-powered automation pipelines that eliminate manual processes — from data ingestion and reconciliation to report generation and anomaly detection
• Build and maintain agentic AI systems that augment trader workflows, including automated monitoring, alerting, and recommendation engines

Technology & Architecture

• Architect scalable, production-grade Python systems on a modern, greenfield infrastructure stack — no legacy systems, no tech debt to inherit
• Build on AWS-native infrastructure (S3, Redshift, Lambda, Airflow/MWAA) purpose-built for quantitative finance workloads
• Leverage Claude Code as the primary development environment — AI-assisted coding end-to-end, from prototyping through production deployment
• Access custom-built global AI agents developed by the team that provide a best-in-class developer experience: automated testing, code review, deployment pipelines, and intelligent tooling that accelerates every stage of development
• Build interactive dashboards and real-time analytics platforms used daily by the trading desk
• Own the full development lifecycle: research → prototype → production → monitoring

Global Quant Team Partnership

This role sits within a unified Global Quant team (New York + London) that operates as one unit. You will:

• Collaborate with London-based quants on shared models, analytics infrastructure, and tooling
• Contribute to and benefit from a shared quantitative library and reusable component ecosystem
• Participate in cross-regional knowledge sharing — what is built once is deployed globally
• Lead and define technical roadmap alongside global leadership

What Sets You Apart

Required

• Advanced degree (MSc/PhD) in Mathematics, Physics, Computer Science, Engineering, or quantitative discipline
• 5+ years' experience in a quantitative role within Equity Swaps, Prime Brokerage, Securities Finance, or a quantitative hedge fund
• Expert Python developer — production-quality code, not just notebooks
• Strong foundation in statistics, optimization, and financial mathematics
• Client-facing experience — comfortable presenting quantitative solutions to sophisticated institutional investors
• Demonstrated ability to communicate complex quantitative concepts to traders, senior management, and non-technical stakeholders
• Self-starter mentality — thrives with autonomy and takes ownership of outcomes

Highly Valued

• Hands-on experience with machine learning in production (scikit-learn, XGBoost, PyTorch, or equivalent)
• Familiarity with large language models, prompt engineering, and AI-assisted development workflows (e.g., Claude Code, Copilot)
• Experience building automation pipelines and intelligent systems that reduce manual overhead
• Cloud infrastructure experience (AWS — S3, Redshift, Lambda, Airflow/MWAA)
• Knowledge of derivatives pricing, funding curves, or collateral management models
• Experience with real-time data systems, event-driven architectures, or streaming analytics

New York, NY Full Time Salary Range of $175,000 - $300,000.