Quantitative Research Summer Intern (Hong Kong)

Quantitative Research Summer Intern (Hong Kong)

Millennium participates in major markets around the world and works to continually evaluate new strategies that fit our risk and return characteristics. We work to maintain agility at scale, which enables us to pursue new investment opportunities in a meaningful way. Our Quantitative Research Interns work within our Investment Teams to help build and grow their businesses.

Job Responsibilities

• Explore and analyze a vast array of datasets, including both market data from asset trading and alternative data from other aspects of the economy using machine learning/statistical/applied math/econometric techniques
• Apply statistical and machine learning techniques to test investment ideas
• Collaborate with portfolio managers, quantitative researchers, and software engineers to deploy these investment ideas and make an impact on the team's Pn L.
• Analyze financial data and develop predictive models to support decision making within the team
• Implement and develop machine learning algorithms to be leveraged in the investment process
• Collaborate with the team to identify opportunities for process improvement and innovation
• Build broad set of research tools for systematic portfolio managers ranging from data acquisition/normalization libraries to backtesters and portfolio optimizers

Qualifications, Skills and Requirements

• Cumulative GPA of 3.5 and above required
• Pursuing a master's degree in a technical or quantitative discipline; such as Financial Engineering, Quantitative and Computational Finance, Statistics, Mathematics, Physics, or Computer Science
• Demonstrated proficiency in at least C++ or Python
• Experience performing an in-depth research project examining real-world data

Preferred Experience

• Independent thinker who can creatively approach data analysis and communicate complex observations in a simple and intuitive manner
• A background in finance is not necessary. We can teach the financial aspects of the job if you display the necessary quantitative skills

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Job ID REQ-22166