Quantitative Trading & Research – Prime Finance Quantitative Research – Vice President

Overview

In this VP role, you will design and implement advanced quantitative models to optimize revenue, manage risk, and automate workflows within Prime Finance. You’ll work closely with trading, technology, and risk teams to deliver impactful analytics and scalable tooling. The role blends ML, statistics, and operations research to forecast borrow rates, price and allocate inventory, and develop alpha signals. You will mentor peers and communicate complex concepts to senior stakeholders, shaping critical business decisions.

Responsibilities

• Develop and implement mathematical, statistical, and ML models to optimize revenue and profitability for stock borrow-loan, cash, and synthetic financing books
• Apply operations research and optimization to automate and enhance traders’ decision-making and inventory management
• Analyze market data to uncover patterns and inform business strategy
• Research alpha signals and automated hedging strategies for systematic trading and datasets
• Collaborate with trading, technology, and risk teams to deliver quantitative tools and solutions
• Build and maintain robust infrastructure for model deployment and analytics delivery
• Ensure models and analytics meet rigorous control and risk standards
• Continuously improve existing models in response to evolving business needs
• Communicate complex quantitative concepts to senior stakeholders and non-technical audiences
• Mentor junior team members and contribute to a collaborative environment
• Document models, methodologies, and processes for transparency and knowledge sharing

Key requirements

• Advanced degree (Masters or PhD) in Statistics, AI/ML, Computer Science, Operations Research, or related quantitative field
• Significant experience in quantitative modelling, analytics, or related roles
• Strong background in AI, ML, OR, or revenue/yield management
• Proficiency in Python for data analysis, modelling, and software development
• Deep understanding of statistics, AI, and optimization techniques
• Proven ability to solve complex quantitative problems and deliver business impact
• Excellent communication and presentation skills with senior stakeholders
• Ability to work collaboratively in cross-functional teams
• Strong organizational skills and attention to detail
• Experience with large-scale data analysis and visualization tools

• excellent communication and presentation skills
• collaboration and teamwork
• mentoring and leadership
• Python for data analysis and modeling
• Machine learning frameworks (scikit-learn, TensorFlow, PyTorch)
• Statistics and optimization techniques

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