MACHINE LEARNING RESEARCHER
Job Title: Quantitative Research and Machine Learning Engineer
We are seeking a highly motivated and skilled Quantitative Research and Machine Learning Engineer to join our hedge fund. This unique role at the intersection of quantitative research and machine learning engineering requires a deep understanding of both domains to drive innovation and data-driven decision-making.
Quantitative Research Integration: Collaborate with quantitative researchers to incorporate statistical analysis, econometrics, and financial modeling insights into machine learning projects. Translate quantitative research findings into actionable machine learning strategies.
Machine Learning Development: Develop, implement, and fine-tune machine learning models that leverage quantitative research methodologies. Ensure the models are statistically robust, accurate, and aligned with economic and financial theories.
Data Processing: Work on data preprocessing, feature engineering, and data cleaning to create high-quality datasets for machine learning projects. Optimize data pipelines to handle large-scale financial data efficiently.
Algorithmic Trading Strategies: Design and develop algorithmic trading strategies that adapt to changing market conditions, optimize portfolio management, and manage risk effectively. Monitor and improve the performance of trading algorithms.
Collaborative Research: Collaborate with cross-functional teams to apply the quantitative research and machine learning expertise to various domains, beyond finance, such as healthcare, marketing, and more.
Continuous Learning: Stay up-to-date with the latest developments in quantitative research and machine learning techniques. Continuously expand knowledge and skills to remain at the forefront of the field.
- Master's or Ph.D. in Quantitative Finance, Statistics, Economics, Computer Science, or a related field.
- Strong background in quantitative research, including statistical analysis, econometrics, and financial modeling.
- Proficiency in machine learning techniques, including supervised and unsupervised learning, time-series analysis, and deep learning.
- Experience with programming languages such as Python or R for data analysis and machine learning.
- Knowledge of data engineering techniques for data preprocessing and feature engineering.
- Familiarity with financial markets, trading strategies, and risk management.
- Excellent communication and collaboration skills to work closely with both quantitative researchers and machine learning engineers.
- Proven ability to work in a dynamic, fast-paced environment and adapt to changing project requirements.
Why This Fund?:
- Join a forward-thinking organization that values innovation and data-driven decision-making.
- Collaborate with a diverse and talented team at the forefront of quantitative research and machine learning.
- Opportunity to work on cutting-edge projects that have a significant impact on various industries.
- Competitive compensation package and career growth opportunities.
If you are passionate about merging quantitative research with machine learning engineering to drive real-world impact, we encourage you to apply for this exciting position. Join us in shaping the future of data-driven decision-making.
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