Quantitative Strategist

Job Overview

A Global Asset Manager is looking for a Quantitative Strategist to join the team. You will work as an individual contributor and partner closely with investment professionals to deliver high-impact projects supporting trading, alpha generation, risk management, portfolio analytics, and investment decision-making. The ideal candidate has excellent problem-solving skills, strong quantitative and programming capabilities, and the ability to collaborate effectively with both technical and non-technical stakeholders. This opportunity is suited to someone who values thoughtful innovation, high-quality execution, and the ability to directly influence investment technology and quantitative infrastructure.

Major Responsibilities

• Develop real-time P\&L and risk management systems.
• Build interactive analytical tools for portfolio management teams.
• Work with portfolio managers and investment professionals to implement trading signals across a wide range of asset classes.
• Partner with portfolio managers and analysts to identify opportunities where AI, quantitative technology, and advanced analytics can enhance research, risk management, and decision-making.
• Provide quantitative technology support for investment projects, including reporting, backtesting, model development, and implementation of new strategies.
• Develop and implement quantitative models and analytical frameworks.
• Analyze large datasets to identify patterns, trends, and investment opportunities.
• Collaborate with technology and investment teams to productionize quantitative research.
• Communicate complex technical and quantitative concepts effectively to both technical and non-technical stakeholders.

What We Value

• 2\+ years of experience in a front-office-focused quantitative development, quantitative research, or quantitative strategy role.
• Advanced degree in Physics, Engineering, Mathematics, Mathematical Finance, Computer Science, or a related quantitative field.
• Strong proficiency in Python and commonly used data-analysis libraries such as Pandas and NumPy.
• Exposure to additional programming languages such as C#, R, or similar languages.
• Strong proficiency with SQL.
• Experience working with financial data, quantitative models, or investment analytics.
• Understanding of financial markets, portfolio management, trading, and risk concepts.
• Strong analytical and problem-solving abilities.
• Ability to work independently while collaborating effectively with portfolio managers, analysts, quantitative researchers, and software engineers.
• Strong written and verbal communication skills.
• Ability to translate complex business and investment requirements into practical technical solutions.