Quantitative Researcher

Engineers Gate is a leading quantitative investment company focused on computer-driven trading in global financial markets.  We are a team of researchers, engineers, and financial industry professionals using sophisticated statistical models to analyze data and identify predictive signals to generate superior investment returns.  EG’s investment teams each focus on their independent strategies while utilizing the firm’s proprietary, state-of-the-art technology and data platform to optimize their alpha research.  We are passionate about implementing scientific and mathematical methods to explore, isolate, and solve problems in the global financial markets.  We believe that career fulfillment and enterprise success converge when smart  hard-working, and intellectually curious people come together with a shared goal of innovation and the pursuit of excellence.

The Team

The researcher will join a small team led by a Portfolio Manager with 15 years of experience developing systems to apply machine learning to petabyte-scale problems in production environments, and nearly 10 years of experience developing predictive models in the global equity markets. The team has a focus on systematic intraday short term and medium term equity strategies that have a statistical edge without being latency-sensitive.  A successful candidate will work closely with the Portfolio Manager and have exposure an extensive and mature technology portfolio that includes distributed machine learning research, analysis, and backtesting systems that should enable applicants to quickly make a direct impact on the P&L of the team with little to no operational burden

Job Summary

The principle focus of this role will be to apply sound financial intuition as well as statistical knowledge to develop and backtest new models for intraday equity prediction.  The researcher will be responsible for collaborating with other team members to explore, analyze, and extract value from a large number of datasets from our existing data platform.  Successful candidates will utilize the existing distributed machine learning and analysis tools to do large-scale equity alpha research for predictive modeling, optimization, as well as to aid in the development of new tools to shorten the research loop. 

Responsibilities

• Utilize statistical learning techniques to explore and analyze a large and diverse set of datasets
• Combine financial and statistical intuition to develop new features and models to be used in our investment process
• Collaborate with the PM to suggest new directions and methods to improve our trading and research processes

Required Skills

• Advanced degree in Computer Science, Engineering, Applied Mathematics, or related STEM field. Bachelors from a top university with relevant years of experience also considered. 
• Strong programming background with proficiency in Python, Pandas, Numpy and related scientific computing technologies
• Competent with version control, release cycles, and unit testing
• Strong communication skills

Preferred Skills

• Experience managing the development and deployment of machine learned models in a production environment
• Strong data experience including fitting models with financial data

The salary range for this role is anticipated to be between $125K and $150K.  This range does not include any potential bonus amounts, other forms of compensation, or benefits offered.  Actual compensation for successful candidates will be carefully determined based on a number of factors, including the candidate’s skills, qualifications, education and experience.