Quant Trader

Quantitative Trader: Hillroute Capital About Hillroute Hillroute Capital is a regulated quantitative hedge fund specializing in global digital asset trading. We leverage sophisticated quantitative methodologies and advanced technology to achieve exceptional risk-adjusted returns. Our transparent approach and diverse, experienced team allow us to excel in the rapidly evolving digital asset market.

About The Role We are seeking a highly skilled Quantitative Trader to develop, test, and refine systematic trading models across global digital asset markets. This role offers flexibility in approach—candidates with expertise in systematic strategies, options trading, statistical arbitrage, backtesting, or machine learning are equally encouraged to apply.

Key Responsibilities

• Strategy Development & Backtesting: Design and rigorously backtest quantitative trading models, ensuring predictive reliability and strong risk management.
• Quantitative & Statistical Analysis: Apply advanced statistical modeling, econometric analysis, or financial mathematics to extract market insights.
• Risk Management: Contribute actively to robust risk management frameworks, identifying potential risks and implementing mitigation strategies.
• Innovation: Regularly generate and test new ideas and strategies, pushing boundaries to enhance fund performance.

Preferred Qualifications

• 3–5 years experience in quantitative analysis, trading, or research roles within finance.
• 1-3 years experience in running quantitative machine learning models.
• Advanced degree in quantitative disciplines (Mathematics, Physics, Statistics, Computer Science, Engineering).
• Strong Python programming skills (NumPy, Pandas), and familiarity with backtesting frameworks (Backtrader, QuantConnect).
• Solid knowledge in options pricing, volatility modeling, statistical arbitrage, or systematic strategies.
• Familiarity with financial data platforms (Bloomberg, Refinitiv, Quandl).
• Exposure to cloud computing environments (AWS, GCP, Azure).
• Experience or interest in applying machine learning techniques (XGBoost, TensorFlow, PyTorch) is a plus—but not mandatory.
• Participation in Kaggle or similar platforms is beneficial but not required.

Key Performance Indicators (KPIs)

• Model profitability and risk-adjusted returns.
• Backtest reliability and accuracy.
• Effectiveness in risk management.
• Contribution to innovation and research quality.

What We Offer

• Competitive compensation and performance-based incentives.
• The opportunity to pioneer quantitative strategies in the dynamic digital asset industry.
• A collaborative, inclusive, and flexible working environment.
• Professional growth in an innovative, fast-paced hedge fund setting.

If you're passionate about quantitative finance and thrive in a dynamic, data-driven environment, we invite you to join our team.