Quantitative Researcher
Role description:
Binomial Technologies is looking for a part-time, unpaid Quantitative Research Assistant to contribute to the development of systematic investment strategies and research-driven publications. This is an entrepreneurial opportunity to work alongside a young fund building next-generation quantitative infrastructure. You’ll help shape live research projects, backtest trading signals, explore market anomalies, and contribute to the development of proprietary models that blend finance, math, and data science. This role is ideal for someone with a strong analytical background who wants real exposure to hedge fund-style quant research in a fast-moving, innovation-driven setting. Position can convert to a full-time paid position, however this isn't guaranteed.
What we're looking for:
Background in Mathematics, Computer Science, Engineering, Finance, or related field
Proficiency in Python (including NumPy, Pandas, Matplotlib, and backtesting libraries)
Solid understanding of statistics, probability, and time series analysis
Interest in systematic trading, factor models, or market microstructure
Strong analytical and problem-solving mindset
Ability to work independently and iterate quickly on research ideas
Bonus: Experience with Jupyter, QuantConnect, Zipline, or published academic work
Key responsibilities:
Assist in the development, refinement, and testing of quantitative trading strategies
Analyze financial time series data to identify patterns and edge
Support model design, signal generation, and performance analysis
Help prepare internal research reports and public-facing publications
Contribute to codebases for strategy backtesting and data visualization
Collaborate with the fund’s team on idea validation, robustness checks, and documentation
