Intern, Quantitative Analytics / Machine Learning

Intern - IM

New York, NY

Cowen Investment Management is looking for an Intern to join the Cowen Sustainable Investments team.  The role will work closely with both the portfolio team and the technology team at Cowen. 

The objective is to design technology systems in Python/.NET and build data analytic tools for cross-asset class investment group at Cowen. The project involves building and improving existing quantitative models that focus on statistics, machine learning and deep learning, coordinating with technology group to incorporate quantitative models into web-based user interface, and others as needed.

The strategy is focused on sustainable investing with an ESG (Environmental, Social and Governance) mandate.


  • Clean, analyze, and visualize large data sets.
  • Perform exploratory data analysis to facilitate decision making process of the investment team in both deal-specific and non-deal specific scenarios.
  • Build Machine Learning and Deep Learning Models to improve existing product features and develop new ones.
  • Coordinate with technology team on platform architecture and workflow pipelines in production.
  • Document scripts/models/libraries and testing process.
  • Build valuation, risk management, capital structure arbitrage and other financial models.



  • Must be enrolled in an undergraduate or graduate program in a quantitative field such as Computer Science, Statistics, Economics, Mathematics, or similar quantitative discipline.
  • Experience with traditional as well as modern machine learning/statistical techniques, including Regression, Classification, Regularization, Ensemble Methods, Deep Neural Network, Causal Inference, and Hypothesis Testing
  • Experience with programming languages, such as Python, R, Matlab, Java, C/C++, Python preferred
  • Experience in sourcing, cleaning, manipulating and analyzing large-scale dataset
  • Experience in SQL and NoSQL database is preferred but not required
  • Having basic knowledge in Finance is preferred but not required
  • Distinctive problem solving and analytical thinking
  • Creative and passionate
  • Self-driven and detail-oriented
  • Strong analytical and programming skills
  • Demonstrated ability to work cooperatively with team members
  • Ability to work independently in a fast-paced environment
  • An exceptional work ethic