Data Trading Analyst Summer Internship - 2027 [New York]

Data Trading Analyst Intern

Quantbot Technologies is a leading global quantitative investment firm deploying systematic strategies across asset classes. The firm combines large-scale research supported by advanced computing infrastructure and extensive market and historical data with rigorous scientific methods and modern statistical and machine learning techniques to discover, test, and implement novel investment ideas.

As a Data Trading Analyst Intern, you will work with the Quantbot Data Trading Lab team, a technical group specializing in trading operations, data science, and problem-solving. You will evaluate new datasets, utilize Quantbot’s cloud environment to write and maintain Python scripts, work directly with the New York team to process and assess new datasets, and help develop new tools and infrastructure.

Responsibilities

• Conduct exploratory data analysis on alternative datasets to identify potentially predictive signals
• Perform statistical analysis, including correlation studies, regression analysis, and time-series modeling
• Build ETL processes to integrate new data sources with existing research infrastructure
• Develop data quality monitoring tools to detect anomalies and ensure dataset integrity
• Optimize existing scripts for performance and scalability
• Build internal Python libraries or tools to standardize common analytical workflows across the team

Requirements

• Enrollment in a Bachelor’s or Master’s program in Computer Science or a Data Science-related field (juniors and seniors encouraged to apply)
• Advanced proficiency in Python
• Proficiency in SQL
• Experience with Linux or UNIX environments
• Finance knowledge is beneficial but not essential

Program Details

This 10 to 12-week program runs from June to August and includes training and support with a dedicated mentor. Successful interns may receive full-time job offers.

Compensation

The annual base pay for this role is expected to be between $70,000 and $95,000, prorated based on internship start and end date. The expected range is based on information available at the time this post was generated. Actual compensation for the successful candidate will be determined based on a variety of factors such as skills, qualifications and experience, and level of education.