Quant / Data Scientist (Arbitrage Trading) in InTune Analytics

InTune Analytics is building a collaborative, growth-oriented environment focused on advancing quantitative research and production-grade trading systems. The role sits at the intersection of quantitative research, data science, and systems engineering, with a strong emphasis on turning research into scalable, capital-deployable strategies. You will work with large, noisy datasets from exchanges and inventory systems to identify pricing inefficiencies and translate them into systematic trading and capital allocation models. Collaboration with leadership, engineers, and analysts will be essential to continuously optimize capital deployment across our investment portfolio. This position is ideal for a creative, technically strong candidate who has built trading strategies, backtests, simulations, or optimization models—whether in a professional setting or personal projects.

We are seeking candidates with a strong quantitative background and hands-on programming experience. A Master’s degree in a quantitative field (e.g., Mathematics, Computer Science, Statistics, Physics) or equivalent professional experience is preferred. Candidates should have at least 2+ years in a quantitative, data science, or algorithmic role and demonstrate strong problem-solving abilities with the capacity to explain complex concepts to non-technical stakeholders. Proficiency in Python is essential, with the ability to move between research notebooks (e.g., Jupyter) and production-grade code. Solid SQL skills (including joins, aggregations, window functions, and case logic) and experience working with complex JSON data are required. Comfortable working in a Linux-based environment, including Docker, and familiarity with AWS services (EC2, SageMaker, AWS CLI, S3 workflows) are highly desirable. A natural curiosity about markets and a track record of building trading strategies, backtests, simulations, or optimization models—whether professionally or personally—will help you excel in this role. You should be a creative thinker who thrives on collaboration with engineers and analysts to deliver measurable impact on P&L and risk controls.