Quantitative Researcher - Investment CTA/Fixed Income

Squarepoint Capital•New York, NY

11d•$170,000 - $255,000•Onsite

About The Position

Squarepoint Services US LLC seeks a full-time Quantitative Researcher, Investment/CTA Fixed Income for its New York, NY location. This role involves conducting research on systematic trading strategies for global fixed income markets, analyzing financial data to identify trading ideas, and building predictive models using statistical and econometric methods. The researcher will also backtest strategies, collaborate with engineers for production implementation, and contribute to the analytics and simulation platform.

Requirements

Minimum of Master’s degree, or foreign equivalent, in Science, Technology, Engineering, and or Mathematics (STEM), Finance, Economics or related field of study.
At least two (2) years of experience as a Quantitative Researcher, Associate or related occupation for a financial /investment management/investment banking organization.
Experience with new signal and strategy research and new dataset analysis by applying statistical inference and regression.
Experience evaluating risk and performance of interest rate swaps as research groundwork.
Experience with dataset analysis and parameter selection using statistical tools - Lasso.
Experience using time series basis, cointegration, time series prediction to conduct time series analysis for signal research.
Experience coding algorithms in Python or C++.
Experience reading and writing from databases in SQL, Postgres or kdb.
Experience specifying portfolios with risk characteristics.
Experience using JIRA, git and git management platforms (Gitlab or bitbucket).

Responsibilities

Conduct research on systematic trading strategies to trade securities in global fixed income markets.
Empirically analyze global financial data to identify systematic trading ideas.
Use statistical and econometric modeling methods to quantitatively build predictive models for market movement forecasts and security trading.
Conduct analysis on trading ideas models using quantitative and statistical tools.
Conduct backtesting and assess trading strategies under realistic market assumptions.
Work with engineers to implement trading strategies in production.
Apply programming skills in Python to conduct research, analyze data, and develop models.
Contribute to the analytics and simulation platform by developing research and portfolio construction tools.
Use version control tools like Git, Unix/Linux for development.
Monitor the production process.