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(more about Two Sigma)
Quantitative Researcher
Note: Company “Hybrid” work attendance policy: In-office work attendance required at the aforementioned office address for “collaboration days” based on each team’s requirement; telecommuting/working from home is permissible for remainder of the same month.
Duties: Apply quantitative financial analysis/statistical analysis/data analysis skills, including estimation methods, time series analysis, and machine learning methods to research, formulate, design, and develop sophisticated predictive quantitative financial investment models and financial trading strategies to trade options. Research, design, and develop production-quality, high-reliability, highly tuned numerical quantitative code. Analyze requirements to determine feasibility of quantitative financial trading strategy design. Predict and measure outcome and consequences of financial strategy design. Originate new trading ideas and quantitative models with knowledge of financial market empirical anomalies through latest research findings in quantitative finance literature. Research, analyze, develop, and execute data-driven solutions to financial investment problems. Generate hypothesis and design customized financial research metrics to analyze market impact and construct mathematical/statistical models for prediction and evaluation. Conduct quantitative research on execution quality, adverse selection analysis, and trading cost models of options trading algorithms running across different trading tactics. Improve execution costs by performing quantitative and statistical analysis using different derived data sets, alternate data sources and derived trading data to identify revenue-generating opportunities. Decompose P&L across different execution tactics to help understand better execution quality across these different execution venues. Perform computer software design and full implementation of life cycle for real-time options and equities trading systems based on different market intelligence services.
Minimum requirements: PhD Degree in Finance, Statistics, Mathematics, Computer Science, or related quantitative field plus knowledge of the required skills listed below.
Alternative minimum requirements: Master’s Degree in Finance, Statistics, Mathematics, Computer Science, or related quantitative field plus 3 years of experience in Quantitative and Alpha Research positions and knowledge of the required skills listed below.
Skills required: Must have knowledge of the following quantitative skills and technologies: programming language (C, C++, Java, or Python); machine learning algorithms and ability to tweak them as needed; machine learning applications to real-world datasets; options datasets research; principles of mathematical, statistical, and financial modeling; time-series and large datasets analysis; parameters estimation using machine learning techniques; mathematical modeling including analytical derivations and numerical simulations; stochastic processes; perturbation analysis and harmonic analysis; statistical inference and optimization; algorithms and numerical methods; linear algebra and Partial Differential Equation numerical solvers; options pricing theory and analyzing P&L, inventory, and risks; C++ and Python (including NumPy, SciPy, pandas, linear algebra, and plotting packages); Linux, Bash, and version control systems; and US stocks, ETFs, indices, futures, VIX futures, and options traded on these underliers. Must have published quantitative research work in academic journals and/or presented research at industry conferences (at least 3 papers). Must also pass company’s required skills assessment.
Base salary: The base pay for this role will be between $165,000 and $300,000 per year. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.
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