Quantitative Researcher, Volatility

Job Overview Squarepoint Services US LLC seeks a Quantitative Researcher for its New York, New York location. Responsibilities 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. Qualifications 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. Squarepoint is an EEO/AA employer. #J-18808-Ljbffr