Quant Analyst

What is Hillroute?

Hillroute Capital is a regulated quantitative hedge fund, specializing in global digital asset trading. With cutting-edge technology and advanced quantitative techniques, we achieve exceptional risk-adjusted returns. Our collaborative approach with trusted service providers ensures transparency and effective communication.

Our team of seasoned, global professionals excels in the fast-paced digital asset industry, with expertise in quant trading, risk management, and machine learning. Hillroute's impressive track record demonstrates our ability to push boundaries and deliver outstanding results.

If you're passionate about innovation, inclusivity, and making a meaningful impact, you've found your home at Hillroute.

We are seeking a highly skilled and experienced Quantitative Analyst with expertise in machine learning and deep learning experimentation. The ideal candidate should have a strong background in quantitative analysis and a deep understanding of financial markets. They should possess excellent mathematical and statistical skills, as well as proficiency in machine learning frameworks such as XGBoost and TensorFlow. Candidates with a background in Kaggle competitions or similar data science challenges will be preferred.

Key Responsibilities:

• Model Development and Backtesting: Develop, refine, and backtest quantitative trading models, leveraging machine learning techniques to enhance predictive accuracy and risk management.
• Quantitative Analysis: Conduct in-depth quantitative analysis of market data, including time series analysis, statistical modeling, and econometrics.
• Machine Learning Applications: Apply machine learning techniques to extract insights from large datasets, identify patterns, and develop innovative trading strategies.
• Data Analysis and Visualization: Analyze and visualize complex data to identify trends, anomalies, and opportunities.
• Risk Management: Contribute to the development and implementation of robust risk management frameworks to mitigate potential risks.

Preferred Qualifications:

• 3 years of experience as a quantitative analysis in a financial institution or a trading desk.
• Advanced degree in a quantitative field (e.g., Mathematics, Statistics, Physics, Computer Science, Engineering)
• Strong programming skills in Python, including proficiency in numerical computing libraries (NumPy, Pandas) and machine learning frameworks (scikit-learn, TensorFlow, PyTorch)
• Solid understanding of statistical modeling techniques, time series analysis, and econometrics
• Experience with backtesting frameworks and tools (e.g., backtrader, QuantConnect)
• Strong problem-solving and analytical skills
• Attention to detail and ability to work independently
• Excellent communication skills, both written and verbal
• Experience with machine learning techniques, including supervised and unsupervised learning
• Knowledge of quantitative trading strategies, such as mean reversion, momentum, and statistical arbitrage
• Familiarity with financial data sources and APIs (e.g., Bloomberg, Refinitiv, Quandl)
• Experience with cloud computing platforms (e.g., AWS, GCP, Azure)

• Demonstrated enthusiasm for applying machine learning to develop innovative trading strategies
• Proven experience in developing and improving trading strategies using quantitative analysis techniques
• Experience with backtrader
• Exposure to Kaggle competitions or similar data science communities

Key Performance Indicators (KPIs):

• Model Performance: Profitability, risk-adjusted returns (Sharpe ratio, Sortino ratio), and other relevant metrics.
• Backtesting Accuracy: Accuracy of backtests in predicting future performance.
• Time to Market: Speed of implementing new models and strategies.
• Risk Management Effectiveness: Ability to identify and mitigate risks.
• Innovation and Contribution: Contribution to new ideas, research, and improvements.

• Chance to work in a hedge fund as a Quantitative Analyst specializing in digital assets.
• Competitive financial rewards and Annual PLI (Performance LinkedIn Incentive)
• Be part of the forefront of an emerging and high-growth market.
• Utilize your strong quantitative skills to navigate the complex and dynamic nature of digital assets.
• Develop cutting-edge trading strategies and analyze vast amounts of data.
• Contribute to generating high returns for our fund and investors and get rewarded for it.
• Although we work from our office in New Delhi, we are flexible in our style and approach