Columbia Investment Management Company, LLC, ("IMC") is a wholly-owned subsidiary of Columbia University charged with stewarding Columbia's endowment for the current and future support of University operations and with preserving the purchasing power of the endowment over the long-term after inflation. Almost all assets across the $10B+ endowment are managed externally in a diversified strategy that uses active and passive management techniques across a wide range of asset classes.
The IMC seeks professionals who can contribute materially to the management of the portfolio. Independent thinking and open dialogue are actively encouraged, with team members contributing to the skills, thinking, qualitative and quantitative analysis related to the overall portfolio, including equities, real estate, other real assets, private equity and a variety of public market strategies. The IMC environment is one in which staff members are expected to develop professionally, work collaboratively, and assume greater responsibilities according to ability and impact.
Columbia IMC is looking to add a data scientist to the investment team. The IMC has a long history of using data to support investment decision making (centered on manager selection) and is continually growing and refining its use of data and scientific methods. We are looking for someone who can think independently and work creatively with data. The IMC data science effort is integrated into the investment team and is an active contributor to real and material investment outcomes. We operate a modern data science platform (JupyterHub-based on AWS) and work primarily in Python in the PyData stack with tabular, relational, time series, and text data. This is a hands-on and very visible position. As a consequence of the responsibilities below, the incumbent will be impactful in our collaborative investment deliberations and will learn and enhance our unique approach to endowment portfolio management.
Perform exploratory data analysis, build models, and run experiments to generate data-driven insights across asset classes and geographies which validate or reject our investment hypotheses and refine our assumptions and inputs for all stages of our investment process.
Author production-grade reports, analytics, and dashboards for the above and for portfolio risk measurement.
Work on studies and models to encode and automate portions of our investment process.
Interface with data vendors: evaluate the information content of datasets large and small and work with our data engineering team to onboard/ingest/map data.
Become a resident expert in our data science platform, existing datasets, and schemas.
Bachelor's degree in a scientific or technical discipline or equivalent and a minimum of three years related experience required.
2+ years working in an applied data analysis capacity required
Fluency (evidenced by academics, projects, work experience, MOOCs, etc.) in data science foundations including probability and statistics, software engineering practices, version control with git & GitLab/GitHub, basic Linux CLI/bash, and Jupyter notebooks
Excellent written and verbal communication and presentation skills applied to data visualization, storytelling, and dashboarding (Python stack, Tableau)
Tabular and time series data manipulation and analysis in Python/pandas and SQL
Familiarity with machine learning methods and the model building/evaluation process (e.g., familiarity with clustering, regression, tree-based modelling, dimensionality reduction, pipelines, and cross validation in scikit-learn)
Experience working with data in the "real world" (e.g., gathering, cleaning, joining datasets; understanding the assumptions and limitations of common modeling techniques; working with uncertainty in predicted quantities or class membership; presenting to stakeholders with diverse backgrounds) and delivering production-grade "data products"
Basic experience with Excel
Commitment to and excitement for continuous learning (e.g., reading papers, attending academic and industry conferences, discovering new packages and tools, learning new and unfamiliar technologies and financial topics, etc.) required.
Must have a passion for excellent customer service and commitment to exceptional quality
D3.js experience is desirable
Institutional financial, risk management, and/or investment domain experience is a plus.
Equal Opportunity Employer / Disability / Veteran
Columbia University is committed to the hiring of qualified local residents.
Internal Number: 505867
About Columbia University
Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the university to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.