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Job Description Quantitative Developer/Engineer as part of a portfolio-management team primarily based in London, with a focus on systematic trading opportunities in global futures and equities. The primary focus of the developer/engineer will be on the development and subsequent optimization of infrastructure supporting the overall development and production of quantitative trading models. This team member will be responsible for the implementation of technology to enable large-scale computational efforts in quantitative research, as well as related efforts, such as the preparation and transformation of data and other operational tasks. This role will work with senior technologists on the design and implementation of systems, and work closely with the quantitative research team to enable their mission. Partner closely with the Senior Portfolio Manager to develop data engineering and prediction tools primarily for the systematic trading of equities
Develop software engineering solutions for quantitative research and trading
Build and maintain robust data pipelines and databases that ingest and transform large amounts of data
Develop processes that validate the integrity of the data
Implementation and operation of systems to enable quantitative research (i.e. large scale computation and serialization frameworks)
Stay current on state-of-the-art technologies and tools including technical libraries, computing environments and academic research
Master’s or PhD in Computer Science, Physics, Engineering, Statistics, Applied Mathematics, or related technical field appropriate to a computational background
Expert in C++
Advanced programming skills in Python
Strong Linux-based development
Extremely strong computer science or engineering background with 3+ years of experience
3-4 years of professional experience in a computer science/computational role
Experience working in a technical environment with DevOps functions (Google Cloud, Airflow, InfluxDB, Grafana)
Design and implementation of front-office systems for quant trading
Knowledge of machine learning and statistical techniques and related libraries
Experience with financial data
As soon as possible
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