Machine Learning Analyst

Responsibilities

• Collaborate closely with Machine Learning team members, portfolio managers, and researchers to translate open-ended investment questions into well-defined analytical and machine learning problems
• Develop and evaluate data-driven machine learning and quantitative models, including simulation- and optimization-based approaches, for investment-related problems
• Contribute to maintaining existing models and analytic tools in production
• Over time, take ownership of individual features and components and full projects
• Clearly document and communicate methods, assumptions, results, and limitations of models to other researchers and trading professionals across the firm
• Stay current with relevant new techniques and technologies in machine learning and artificial intelligence, particularly as they pertain to finance and investing

Qualifications

• Bachelor’s degree (or equivalent) in a rigorous quantitative field
• 0-2 years of experience through industry internships, undergraduate research or thesis, or substantial independent technical projects involving software development, data analysis, or machine learning
• Proficiency in Python and familiarity with the Python data science stack (NumPy, SciPy, Pandas, scikit-learn, etc), with experience in other languages a plus
• Experience working with and analyzing data from multiple sources and in multiple formats
• Familiarity with machine learning and statistical modeling fundamentals, including model evaluation and experimental design
• Demonstrated ability to independently scope and execute open-ended technical projects
• Interest in financial markets, intellectual curiosity, and comfort in working on open-ended problems
• Strong written and verbal communication skills