A systematic investment team is seeking a strong quantitative developer/researcher to join in using statistical and machine learning approaches to build a robust critical trading infrastructure and investment research platform. There will be a focus on applying cutting edge statistical and machine learning techniques to short and medium term systematic, trading strategies in equities markets. Ideally you will want to be based in Chicago but global candidates will be considered .
- Partner closely with the Senior Portfolio Manager to develop data engineering and model prediction tools for systematic trading and monitoring
- Assist in designing, coding, and maintaining tools for the systematic trading infrastructure of the team
- Perform data analysis and generate live and historical analytical reports
- Stay current on state-of-the-art technologies and tools including technical libraries, computing environments and academic research
- Collaborate with the Senior Portfolio Manager and the trading group in a transparent environment, engaging with the whole investment process
- Strongly skilled/expert in Python with at least 3 years of experience.
- Master’s, or PhD degree in Computer Science, Engineering, Applied Mathematics, Statistics or related STEM field
- Strong quantitative skills to leverage while building out quantitative tools for research
- Experience using statistical or machine learning techniques to build a scalable and robust program
- 2-5 years of experience in finance or technology
- Previous exposure to a systematic trading environment or equivalent sell-side experience
- Experience in efficient database management
- Knowledge of machine learning and statistical techniques and related libraries
- Participation in mathematical, programming, or trading competitions
Please send a PDF resume to firstname.lastname@example.org