Gambit Research
Gambit Research, established in 2005 and based in Hammersmith, West London, specializes in software and statistical consulting with a focus on sports. The company utilizes a variety of programming languages and modern open-source technologies, and maintains a flat organizational structure that emphasizes collaboration and teamwork.
Company Overview
Gambit Research is a software and statistical consulting firm established in 2005. The company is based in Hammersmith, West London, with its office located at Colet Court, 100 Hammersmith Road, London, W6 7JP, United Kingdom.
Services
Gambit Research specializes in software and statistical consulting, with a particular focus on sports. The company's expertise in these areas is built on a strong technical foundation, incorporating modern programming languages and data analysis technologies.
Technical Infrastructure
Gambit Research's core platform employs a mix of programming languages including Python, C++, JavaScript, and Erlang. The Erlang language is utilized for its excellent concurrency features, while C++ is used for strategies and critical path components to ensure optimal performance. Backends are primarily written in Python and communicate with the core Erlang system using TCP sockets. Frontend communication is handled via the WebSockets protocol, and interfaces are built using React.
Open Source Contributions
Gambit Research actively contributes to the open source community. Some of the projects they have contributed to include Psycopg, PyPy, Tulip, and AngularJS. Their statisticians make use of modern open source data analysis technologies such as R, IPython notebook, and pandas.
Work Environment and Internships
Gambit Research fosters a collaborative work environment with a flat organizational structure. Developers typically work on desktop machines running Linux distributions like Ubuntu or Debian. The company also offers paid summer internships for talented developers and quantitative analysts, providing opportunities to work with tools like Jupyter, Spark, Pandas, and Pytorch.