Quantitative Researcher, Volatility

Job Overview

Square point Services US LLC seeks a Quantitative Researcher for its New York, New York location.

• Perform independent and complex financial quantitative analysis to formulate mathematical and simulation models of investment strategies, including defining constants, variables, restrictions, alternatives, and numerical parameters.
• Enhance trading through computerized algorithms by implementing models using advanced statistical techniques, machine learning, and statistical inference.
• Develop and implement sophisticated analyses to identify new statistical effects, assess the robustness of these effects, and create quantitative strategies.
• Validate and test both trading simulations and critical trading applications.
• Build applications with Shell and Python to automate daily data dependency processing for trading strategies.
• Utilize KDB/Q and Python to analyze existing strategy behavior, propose improvements, and implement them.
• Use Excel/VBA and KDB analysis tools to track market history for specific asset classes to evaluate future profit potentials and risk margins.
• Manage live trading automatons and continuously monitor risk related to those automatons.
• Leverage asset‑class‑specific experience to uncover new patterns in market data and optimize execution costs.
• Apply extensive knowledge of market structure and statistical arbitrage to improve existing trading strategies and develop new ones.
• Assist senior quantitative researchers in building, validating, releasing, and maintaining highly complex automated trading models.
• Lead research projects spanning multiple teams and regions to develop new mathematical models and analytical tools for critical investment decision making.

• Minimum of a Master’s degree or foreign equivalent in a STEM field and at least 2 years of experience as a Quantitative Researcher, Quant Associate, or related position within an investment/asset management organization.
• Proficiency in performing asset‑specific research and engaging in real trading.
• Experience analyzing time‑series data using techniques such as auto‑correlation, stationarity tests, autoregressive moving average models, and conditional heteroskedasticity modeling.
• Knowledge of portfolio construction and exploration of systematic trading ideas.
• Ability to back‑test strategies and evaluate performance metrics including Sharpe ratio, return over gross, turnover, and drawdown.
• Expertise in implementing back‑test frameworks and automating signal/report generation.
• Strong analytical skills with large datasets using regression, correlation, and other statistical techniques.
• Availability for full‑time (40 hours per week) work.
• Expected base salary range: $145,000 to $185,000 per year.

Square point is an EEO/AA employer.