Junior Quantitative Researcher

AI overview

Develop and evaluate quantitative strategies while analyzing latency optimization logs and back-testing models in a dynamic trading environment, collaborating with traders and engineers.

We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones.

Currently, we are looking for a Junior Quantitative Researcher for Machine Factor Technologies.

About the client:

Machine Factor Technologies is a regulated, market-neutral, multi-strategy algorithmic trading fund operating in the digital assets space. We trade across both CeFi and DeFi markets—spot and futures—leveraging a blend of traditional finance rigor and cutting-edge crypto innovation.

Role Summary:
As a Junior Quantitative Researcher, you’ll partner with our investment team to develop and evaluate crypto‐focused quantitative strategies. You’ll analyze latency‐optimization logs, back-test models in live environments, and deliver data-driven feedback to refine our trading signals. This role is modelled on Citadel’s Quantitative Researcher framework, emphasizing rigorous research, statistical analysis, and rapid implementation of algorithms into code.

Key Responsibilities:

  • Conduct quantitative research on crypto markets and evaluate strategy performance.

  • Analyze large datasets and latency logs to identify bottlenecks and optimize trade execution.

  • Conceptualize and continuously refine mathematical models; translate algorithms into production-ready Python/Pandas code.

  • Back-test and implement trading signals in a live environment, monitoring real-time performance.

  • Collaborate with traders, engineers, and data teams to integrate findings and improve strategy robustness.

Skills & Preferred Qualifications:

  • 1–3 years’ experience in computer science, machine learning, or a similarly quantitative field.

  • Deep proficiency in Python and Pandas for data manipulation and analysis.

  • Strong foundation in statistics and mathematics (e.g., probability, time-series analysis, hypothesis testing).

  • Prior exposure to data-driven research or ML model development.

  • STEM background (e.g., CS, Math, Engineering) is preferred.

  • Knowledge of finance or digital-asset markets is appreciated but not required.

  • Familiarity with unconventional data sources, version control, and automated testing frameworks.

Compensation & Benefits:

  • Discretionary year-end trading bonus.

  • Opportunities for professional growth in an innovative trading environment.

Interview Process:

  • HR Screening: 30-minute introductory call

  • Take-Home Test: Quantitative and coding task (3–5 days’ turnaround).

  • Technical Interview: 1–2 hour deep dive into your research, coding, and statistical approach.

  • Culture Fit Interview: 1 hour with Senior Team Members to assess collaboration style and values.

What’s next?

If this role sounds like a fit — we’d love to hear from you! Just send over your CV and anything else you’d like us to consider.

We’ll review everything within five working days, and if your background matches what we’re looking for, we’ll get in touch to set up a call and get to know each other better.

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