Quant Researcher (Crypto Derivatives)
Role in brief
Midpoint is a proprietary trading desk focused on crypto derivatives. They seek a Quant Researcher to develop and implement trading strategies, leveraging AI in research. Candidates with experience in mid-frequency trading and Python skills should apply.
About the role
Midpoint operates a proprietary trading desk in the cryptocurrency markets, utilizing its own capital. The team consists of graduates from top universities, emphasizing a collaborative and data-driven approach. The firm provides robust infrastructure, including access to historical data and backtesting services.
The Quant Researcher will be responsible for developing trading strategies for both spot and perpetual futures, employing AI agents to enhance the research process. Success in this role involves effectively testing hypotheses, building comprehensive backtests, and transitioning strategies from paper trading to live execution.
Skills that matter here
- Python: This role requires proficiency in Python for data analysis and strategy development.
- data analysis: Candidates will analyze historical data to test trading hypotheses and refine strategies.
- statistics: Working-level statistics are essential for hypothesis testing and assessing result stability.
- AI agents: Experience with AI agents is crucial for automating parts of the research cycle and coding.
Who this role suits
- A candidate with a background in mid-frequency trading and a track record of deploying live strategies.
- Someone comfortable with statistical analysis and hypothesis testing in a fast-paced environment.
- An individual who thrives in an international team and can effectively communicate in English.
From the employer
- Develop strategies for spot and perpetual futures: market-neutral and directional.
- Test hypotheses on historical data: trades, candles, funding, open interest, capitalization.
- Build backtests with honest costs, margin considerations, and overfitting control.
- Use AI agents in the research cycle: hypothesis generation, backtest coding, review, report analysis. The agent's results are verified by a human, and mass hypothesis generation is considered in overfitting assessment.
- Implement strategies through paper trading to live and track discrepancies between live results and backtest.
- Participate in auditing strategies of external quants.
- Experience in mid-frequency trading and deploying strategies in production: your alphas were traded live — you deployed them yourself or your team did.
- Python for data analysis.
- Working-level statistics: hypothesis testing, multiple comparisons, result stability assessment.
- Understanding of crypto derivatives: perpetual futures, funding, basis, margin, and liquidations.
- Experience with backtests that account for commissions, slippage, and lookahead bias.
- Experience working with AI agents for coding and data analysis (Claude Code, Codex, or similar): ability to assign tasks to the agent, verify its code, and not accept results without control.
- English at a level sufficient for reading scientific articles and working in an international team.
- Fixed salary and bonus from the profits of the strategies you brought to live trading.
- Probation period of several weeks, after which the bonus part will be reviewed.
- Ready data and infrastructure: work on strategies, not on loaders.
Questions about this role
What is the remote policy?
The position is fully remote.
What is the seniority level of this role?
This is a middle-level position.
How do I apply for this role?
Details on how to apply are not provided in the input.
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