2026 Summer Intern - Public Affairs & Access: Evidence for Access (Policy, Evidence & Access Strategy) Technical Institute

Roche•South San Francisco, CA

1d•$45 - $50•Onsite

About The Position

Public Affairs & Access is a multi-disciplinary organization that includes Access Solutions & Patient Support; Channel & Contract Management; Corporate Communications; External Affairs; Patient Strategy; Policy, Evidence & Access Strategy; and Strategic Business Operations. Our mission is to drive positive change in the healthcare system so that every patient can access our science. We lead the development of meaningful partnerships, forward-looking pricing, contracting and distribution strategies, and proactive policy solutions that advance a more equitable and hopeful future for all of those who need our therapies. Evidence for Access (E4A) is a Health Economics and Outcomes Research (HEOR) organization that applies diverse expertise to demonstrate the value of our medicines and support optimal patient outcomes. The Technical Institute (TI) acts as a Center of Excellence within E4A, leveraging real-world data, modeling, and innovative technology solutions to deliver data enablement, actionable insights, and strategic impact. TI is looking for a Data Science intern to drive technical innovation within Health Economics and Outcomes Research (HEOR). You will have the opportunity to engage in a variety of activities, including: Business Critical Innovation with Machine Learning - Help develop, refine, and scale custom Machine Learning predictive models on large-scale datasets (100M+ records) to address business-critical problems. An example of potential work includes utilizing ML to address data limitations, such as cost imputation in complex claims data. Help set the groundwork for deployment and “productionization” of technical solutions - With support from and close collaboration with organizational partners, an aspiration for this internship is to help set the groundwork for deployment and “productionization” of model pipelines. Exposure to real-world data and observational research/real-world evidence as well as the US health care system and the pharmaceutical/biotechnology industry. Knowledge sharing with and presentations to key stakeholders, including technical and non-technical audiences. Co-author communications for dissemination at research conference(s) or peer-reviewed scientific journals.

Requirements

You meet one of the following criteria: Must be pursuing a Master's Degree (enrolled student). Must have attained a Master's Degree. Must be pursuing a PhD (enrolled student). Must have attained a PhD.
Required Majors: Computer Science, Data Science, Biostatistics, Bioinformatics, Epidemiology, Health Economics, or related quantitative disciplines.
In-depth knowledge of advanced Machine Learning techniques (e.g., ensemble learning, neural networks) as applied to both structured and unstructured data.
Strong programming skills in SQL and Python or R.
Working proficiency in UNIX/Linux environments, including shell scripting (Bash), and experience working with High-Performance Computing (HPC) clusters for large-scale data processing.

Nice To Haves

Excellent communication, collaboration, and interpersonal skills.
Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.
Prior experience with real-world data (e.g., IQVIA PharMetrics Plus, Truveta, MarketScan, Flatiron EHR etc.).
Prior experience applying advanced Machine Learning methods to real-world healthcare data.

Responsibilities

Help develop, refine, and scale custom Machine Learning predictive models on large-scale datasets (100M+ records) to address business-critical problems.
Help set the groundwork for deployment and “productionization” of model pipelines.
Knowledge sharing with and presentations to key stakeholders, including technical and non-technical audiences.
Co-author communications for dissemination at research conference(s) or peer-reviewed scientific journals.