Research Associate, Data Science

Company Overview

We are a Boston-based investment manager that provides global and international equity investment strategies and fund products to institutional investors such as pension plans, endowments, foundations, and registered/unregistered commingled investment funds. We are a registered investment adviser with the U.S. Securities and Exchange Commission (SEC), and a registered commodity trading advisor and commodity pool operator with the U.S. Commodity Futures Trading Commission (CFTC).  Our firm manages over $90 billion for over 175 client relationships in North America, Europe and Australasia.  Our offices are located at 200 Clarendon Street, Boston, Massachusetts.


The Research Team

Our research group is a collaborative, intellectually rigorous team responsible for coming up with investment ideas, codifying those ideas into signals, back-testing the signals, and producing return and risk forecasts based on the signals to drive trading decisions.  We are looking for a new associate to join our research team. 



  • Performing ad-hoc exploratory statistical analysis across multiple large complex data sets from a variety of structured and unstructured sources
  • Assessing the quality of historical panel datasets, diagnosing deficiencies and prescribing fixes
  • Proposing, designing, and creating software to enhance our data science technology stack
  • Staying up to date on the PyData ecosystem and evaluating new libraries and tools
  • Working with developers to design feeds for new data sources from third-party vendors
  • Writing and maintaining code that supports the investment research production processes
  • Proposing and implementing performance improvements in our data analysis processes
  • Researching predictable patterns in data relevant to financial markets



The ideal candidate will have:

  • An undergraduate or graduate degree from a top educational institution in a technical field, such as data science, applied mathematics, economics, engineering, or computer science
  • Demonstrated professional or academic success (recent graduates are encouraged to apply)
  • Strong analytical, quantitative, and problem solving skills
  • Expert programming skills in Python, C/C++, C#, or Java
  • Expertise in OOP paradigms, data structures, and numerical algorithms
  • 2+ years of experience with data analysis in Python with pandas and numpy
  • Some experience with data analysis in R with tidyverse packages
  • Understanding of probability and statistics, including linear regression and time-series analysis (machine learning skills are not required)
  • Experience analyzing large data sets
  • Curiosity and a willingness to learn new technologies
  • Interest in financial markets  (prior experience not required)
  • Great communication skills, including data visualization

In addition, experience with any of the following would be valuable:

  • Hadoop, Spark, Kafka,  and related technologies
  • SQL
  • Unix/Linux system tools and environment
  • Basic familiarity with unit testing, continuous integration, DevOps, VMs, containerization
  • Interactive data visualization and dashboards, e.g. with Shiny
  • High-performance computing


Qualified candidates should submit a resume to Please include a cover letter detailing your short and long-term career goals and copies of transcripts. No telephone calls please.