Senior Python Quantitative Developer sought by a specialist and multi-award-winning Systematic Hedge Fund in a brand-new Core team designing and implementing a greenfield centralised Python/SQL/Linux/Docker platform for Backtesting, Pricing, Risk and Performance to be used across all Funds and Investment teams.
Our client is an early Quantitative Investment Firm, managing around $10BN+ and with a focus on Scientific Investing and new ideas. They also boast a rare and highly reputable culture and working environment geared towards collaboration and communication, with zero siloes, and industry-leading tenure. The firm totals around 150 staff, all of whom are office-based three or more days per week.
This is a more technical Senior QD role which will involve collaborating with Quantitative Researchers and Portfolio Managers to architect, design and implement scalable solutions, addressing complex business needs. Primarily, you will be charged with delivering and maintaining critical components of the investment infrastructure, including the Data Interface Layer, Central Risk Calculations, and Backtesting Frameworks which will be a key tool for the Investment teams.
Essential Skills & Experience:
* Excellent Quant Development and Python skills, as per 3+ years of professional experience in Financial Markets, ideally in a Systematic Hedge Fund and/or dealing with Futures.
* Quantitative Finance experience and knowledge, preferably with experience in developing financial Backtesting systems for Quantitative Strategies.
* Hands-on experience with continuous integration and delivery systems such as Jenkins and GitLab CI/CD and a strong understanding of Software Development Life Cycle (SDLC) best practices, with knowledge of SQL, Linux and ideally Docker.
* PhD/MSc level education in a numerate discipline from a top institution.
* MATLAB experience highly desirable.
This is an outstanding opportunity to join a world-class boutique Systematic Investment business, playing a key role in the delivery of a crucial core platform for use by cross-functional teams across multiple investment platforms.