Quantitative Researcher

Company Description Algorio is a fintech startup focused on building next-generation algorithmic trading infrastructure for hedge funds, proprietary trading firms, and institutional investors. The company’s platform combines advanced quantitative research with low-latency execution to support precise and scalable systematic trading strategies. Algorio operates at the intersection of finance, mathematics, and technology, offering a highly technical environment for solving complex market problems. Team members collaborate closely on research and development to continually enhance the performance and robustness of the trading systems.

Role Description As a Quantitative Researcher at Algorio, you will design, test, and refine systematic trading strategies using large, complex financial datasets. Day-to-day responsibilities include developing statistical and mathematical models, performing rigorous backtesting, and conducting performance and risk analysis to validate research ideas. You will collaborate with engineering teams to translate research outputs into production-ready algorithms and optimize strategies for low-latency execution. This is a full-time, on-site role based in the Tel Aviv District, Israel, requiring close collaboration with colleagues across research, engineering, and product functions.

Qualifications

• Strong foundation in Statistics and Mathematics, including probability, econometrics, and time-series analysis.
• Demonstrated experience in Quantitative Research and Quantitative Investing, with an ability to design and evaluate systematic strategies.
• Excellent Analytical Skills, including comfort working with large datasets and interpreting complex results.
• Proficiency in programming languages commonly used in quantitative finance (e.g., Python, R, C++, or similar).
• Experience with data analysis tools, numerical libraries, and version control systems.
• Advanced degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics, Engineering, or Finance, or equivalent practical experience.
• Familiarity with financial markets, microstructure, and algorithmic trading concepts is highly beneficial.