Senior Data Science Intern (PhD) - Boston (2026 Start Date)

Analysis Group•Boston, MA

About The Position

Make an impact at Analysis Group, where we provide our clients with thoughtful, pragmatic solutions to their most challenging business and litigation problems. Analysis Group is one of the largest economics consulting firms, with more than 1,500 professionals across 15 offices in North America, Europe, and Asia. Since 1981, we have provided expertise in economics, finance, health care analytics, and strategy to top law firms, Fortune Global 500 companies, and government agencies worldwide. Our internal experts, together with our network of affiliated experts from academia, industry, and government, offer our clients exceptional breadth and depth of expertise. Analysis Group provides economic, financial, and strategy consulting to law firms, corporations, and government agencies. At Analysis Group, Data Science is a center of excellence within a company that already has decades of experience focused on analysis involving data. The Data Science team is charged with collaborating with leading internal and external academic experts to find creative solutions to some of the most challenging and high-value problems we face. We are currently seeking a Senior Data Science Intern to join our team. The ideal candidate should be passionate about working on cutting edge research and analytical services for Fortune 500 companies, global pharma/biotech firms and leaders in industries such as finance, energy and life sciences. The Senior Data Science Intern will be a contributing member to client engagements and have the opportunity to work with our network of world-class experts and thought leaders.

Requirements

Pursuing a PhD is required, preferably in Computer Science, Data Analytics, Data Science, Economics, Mathematics, Statistics, or related subjects
Proven ability to independently apply advanced statistical and mathematical methods to tackle complex research questions and drive meaningful insights
Strong credentials and experience in working with both structured and unstructured data, along with data visualization skills, are required
Proficiency in Python and/or R is required, with project experience in either language
Eagerness and ability to quickly learn new skills, analytical methodologies, and technologies to effectively support and contribute to project teams
Demonstrated experience working on project teams and collaborating with others
Strong interpersonal, written, and oral communication skills
Candidates who will require future visa sponsorship must have valid U.S. work authorization, such as F-1 CPT or J-1 Academic Training, for the duration of their internship and , e xcept in exceptional circumstances , must also be pursuing a STEM-eligible degree.

Nice To Haves

Familiarity with online/cloud computing and storage platforms (e.g., Azure, AWS) is preferred, along with experience working within an HPC environment
Experience working within a Linux environment is a plus, as well as experience with Docker and front-end development using a JavaScript framework (e.g., Vue.js, Angular)

Responsibilities

Working with project teams to address data science/computing challenges
Identifying opportunities for technology to enhance service offerings
Acting as a resource and participating in client engagements and research as part of the project team
Maintaining up-to-date knowledge of computing tools, providing technical training and helping to grow the in-house knowledge base, specifically in a Linux environment
Conducting advanced statistical and mathematical analyses to address complex research questions to derive actionable insights that support client decision-making
Developing data engineering and machine learning production systems for full stack data science projects
Using natural language processing methodologies to work with EMR data, social media data and other unstructured data
Optimizing procedures for managing and accessing large databases (e.g., insurance claims, electronic health records, financial transactions)
Creating interactive analytics portals and data visualizations (e.g., using R/Shiny, Python/Flask, D3)
Leveragingon grid and cloud computing environments, and developing software packages in R, Python, and other object-oriented languages
Establishing optimized procedures for repetitive or computationally intensive tasks (C, C++, Cuda-C)