Quantitative Researcher
Your main job is calibrating our proprietary trading and risk model, improving its metrics and showing that each change makes the reports more accurate on GC, NQ and ES.
About Solo Clash
Solo Clash is a proprietary trading company with a simple mission: give aspiring traders the training, technology, and community they need to succeed, and let them focus on what they do best. We provide the environment; our traders bring the curiosity. Together, we win.
At the heart of our platform is our in-house analytics and trading engine, built to process real-time data and surface transparent statistics that help traders make better decisions.
What you'll do
- Calibrate the model's parameters and features, and measure each change against the current version.
- Improve how the model calculates directional bias, confidence scores, consistency and volatility profiles.
- Validate every change out of sample and test it for look-ahead bias, data snooping and overfitting.
- Track how each report performed after the release, find where the model drifts and correct it.
- Turn feedback from the Trading & Risk Analyst into tested model changes.
- Run event studies on CPI, NFP, FOMC and other releases, measuring the surprise against consensus, across different time windows and market regimes.
- Build and extend research pipelines and backtests in our in-house engine.
- Prepare futures data, including contract rolls, trading sessions and time zones.
- Look for new event types, instruments and features that improve the model.
- Report findings to the product and engineering teams and to clients, including changes that did not work.
What we're looking for
- Junior: recent graduates and current MSc or PhD students.
- Mid: experience in quant research, trading or data science on market data, with at least one research project that went into production.
- Degree in mathematics, physics, statistics, computer science, econometrics or a related field.
- Thorough knowledge of statistics, including hypothesis testing, regression and time-series analysis, and experience calibrating or validating statistical models.
- Python for data analysis (pandas, NumPy) and SQL.
- Clean, reproducible research code kept under version control (Git).
- Experience with financial time-series data from work, research or personal projects.
- Interest in financial markets and macroeconomics.
- You review your own results critically before presenting them.
- You work in a structured way, pay attention to detail and can work independently.
- Good written and spoken English.
Nice to have
- Experience with C++, C#, Java or Rust.
- Experience with futures, options or intraday and tick data.
- Experience with economic calendar data, including consensus forecasts and revisions.
- Background in event studies, econometrics or market microstructure.
- Experience building or using backtesting frameworks.
- Knowledge of Bayesian methods, machine learning or regime detection.
- Experience with Claude Code or other AI development tools.
What we offer
- Compensation based on experience.
- Access to Claude Code and other AI tools.
- Mentoring matched to your experience level.
- Responsibility for your own area of the product.
- Career progression based on performance.
- Training and networking opportunities.
Apply
Send your CV, your GitHub profile or a research sample (thesis, paper or notebook), and a short description of a model or analysis you improved, and how you checked that the improvement was real. You can apply even if you do not meet every requirement.