Job Description

qSpark is looking for a quantitative researcher with a genuine edge in signal research and market microstructure to join our team.

This role demands someone who ships research into live strategies and is laser-focused on strategies that achieve high Sharpe in production.

Responsibilities

• Research, develop, and continuously improve quantitative trading signals across HFT and near-HFT timeframes, with a relentless focus on high Sharpe, deployable strategies
• Design and run rigorous backtests that honestly account for microstructure: spread costs, venue behavior, print filtering, adverse selection, and realistic fill modeling — with the explicit goal of performance that holds up in production, not just on paper
• Collaborate closely with portfolio managers and developers to bring validated research into production and improve live strategies
• Analyze live performance regularly — decompose P&L, identify regime shifts, attribute slippage — and feed findings back into active research
• Take on increasing levels of research leadership over time, including mentoring and setting the direction for research cycles

Requirements

Requirements

• 2+ years of hands-on quantitative research or strategy development in an electronic trading environment, with demonstrated ability to produce high Sharpe strategies that survive live deployment
• Strong applied statistics: Performance estimation, overfitting stress-tests, non-stationarity, and test design under real market constraints
• Fluent in Python for research; C++ familiarity a genuine advantage
• Solid knowledge of market microstructure: TAQ data interpretation, venue differences, short-term price dynamics
• Track record of taking research across the line into live production — not just exploring
• Bachelor's or Master's degree in Mathematics, Statistics, Physics, Computer Science, Computational Finance, or a related quantitative field