A leading hedge fund specializing in Quantitative Research and Trading is looking to onboard a Machine Learning Researcher. The firm leverages cutting-edge technology and data science to drive superior performance in financial markets. As they continue to expand our team, they are seeking a talented and highly motivated Machine Learning Researcher to join our Quantitative Trading Strategies team.
Responsibilities:
Algorithmic Research and Development:
- Conduct thorough research to develop, optimize, and implement machine learning models for quantitative trading strategies.
- Collaborate with a cross-functional team to enhance existing algorithms and develop new models that exploit market inefficiencies.
Data Analysis and Feature Engineering:
- Work with large financial datasets to identify relevant features and signals that can be incorporated into trading models.
- Conduct statistical analysis to evaluate the predictive power of potential features and continuously refine models based on performance metrics.
Model Testing and Validation:
- Design and implement rigorous testing procedures to validate the performance of machine learning models under various market conditions.
- Conduct backtesting and stress testing to ensure robustness and reliability of trading strategies.
Risk Management:
- Collaborate with risk management teams to ensure that machine learning models adhere to predefined risk parameters.
- Develop and implement risk mitigation strategies to safeguard the fund's capital.
Stay Abreast of Industry Developments:
- Keep up-to-date with the latest advancements in machine learning, quantitative finance, and market micro-structure to incorporate cutting-edge techniques into our trading strategies.
Qualifications:
- Advanced degree (Ph.D. or Master's) in a quantitative field such as Computer Science, Statistics, Mathematics, or related discipline.
- 4+ years of experience in applying machine learning techniques to financial markets, particularly in algorithmic trading.
- Proficiency in programming languages such as Python, or C++.
- Strong quantitative and analytical skills, with a deep understanding of machine learning models, statistical modeling and time series analysis.
- Experience with financial data, including tick data, order book data, and market micro-structure.
- Experience with deep learning frameworks such as TensorFlow or PyTorch.
Preferred Skills:
- Knowledge of market micro-structure and algorithmic trading strategies.
- Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders.
