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Job description
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TL;DR
ML Quantitative Researcher (Fintech): Developing and testing hypotheses about market inefficiencies to build predictive models for trading with an accent on feature engineering and data leakage prevention. Focus on designing high-predictive features, implementing reliable production data pipelines, and applying advanced ML frameworks to time-series financial data.
Location: Worldwide Remote
Salary: $6,000 – $8,000 per month gross
What you will do
- Formulate and test hypotheses regarding market inefficiencies and validate them through backtesting.
- Design features with predictive power using statistical transformations and learned representations.
- Determine how model predictions are integrated into trading strategies, such as directional bets or spread convergence.
- Analyze alternative data and time series to identify nonlinear dependencies and signals.
- Develop and maintain reliable data pipelines for production environments.
Requirements
- Deep understanding of ML, specifically the internals of neural networks, deep learning, and gradient boosting frameworks.
- Proven experience in identifying and preventing data leakage, particularly in time-series contexts.
- Strong mathematical foundation in statistics, probability theory, and stochastic processes.
- Proficient Python skills, with experience in pandas, Polars, or streaming data processing.
- Statistical mindset with a clear understanding of method assumptions and failure modes.
- English: B2 level or above
Nice to have
- Graduate of SHAD or a similar top-tier technical or quantitative program.
- Experience in competitive mathematics, physics, or computer science olympiads.
- Demonstrated success in Kaggle or other ML competitions.
Culture & Benefits
- Worldwide remote work arrangement.
- Comprehensive training in finance, covering market microstructure and portfolio construction.
- Opportunity to work with complex alternative data and high-impact trading models.
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