Quant Engineer Quant Developer to work in collaboration with the Research, Portfolio Management and Data teams to develop and implement new models, architect solutions and build powerful analytic tools. This is an exceptional opportunity to help build out alpha, risk, transaction cost and portfolio analysis systems at the firm as part of an entrepreneurial team. The successful candidate will be integral to developing the platform and infrastructure for quantitative models used in our equity products. As a member of the investment team, this person will closely collaborate with PMs, quantitative researchers, and integration analysts. Client supports a hybrid work environment; employees are on-site in the Boston office 3 days a week.
What You'll Be Doing:- Develop, validate and enhance our proprietary forecast, risk, transaction cost and attribution models on our quantitative research and production infrastructure.
- Implement, enhance and support our data platform and modeling infrastructure.
- Work with quantitative portfolio managers to build tools and software libraries to advance analytics platforms using machine learning techniques.
- Build systems to gather, cleanse and integrate data from various sources for research and modelling needs.
- Familiarize yourself with our quant system design, architecture and tool chain, be able to trace/debug/enhance components of an investment system. Learn about Equity Alternatives investment processes and production job workflow.
- Make significant contributions to investment strategies integration project. Help to enhance and optimize existing codebase to run more efficiently in AWS environments.
- Support Equity Alternatives daily operations, client requests and ad hoc enhancements. Enhance object model framework and codebase.
- We're Looking for Teammates With:
- Master's degree with an outstanding academic record in a technical field such as science, engineering or mathematics, with 3+ years of experience as a developer for an investment firm; Bachelor's degree with 5+ years of experience. CFA charter is a plus.
- Hands on development experience in Python (pandas, sklearn, statmodels, cvxopt, etc). Familiar with popular machine learning algorithms and packages.
- Good understanding of software system development life cycles.
- Experience in using and building high performance compute, containers, pipelines/scheduling and their relevant tools.
- Familiar with financial data series, building and optimizing data structures and operating data delivery platforms.
- Advanced analytic skills and the ability to clearly articulate the approach, process and results in verbal, graphical and written form.
- Creativity, enthusiasm, collegiality and the ability to excel in a self-starting environment.
- Strong work ethic and roll up your sleeves attitude to deliver projects under tight schedule.
- Hybrid 3 DAYS ON SITE
