2027 Summer Intern Biostatistics Interactive Benchmarking Platform Cambridge MA

Sanofi • Cambridge, MA

1d • Onsite

About The Position

Sanofi is seeking a highly motivated summer intern to develop an interactive benchmarking platform for predicting placebo responses in Atopic Dermatitis (AD) clinical trials. Using the AD Placebo iDB, an internal database containing historical data across different populations and study designs, the intern will explore the data and develop a predictive modeling framework for placebo response rates and variability in future Phase 2/3 trials. The intern will document, validate, and deploy the framework as a user-friendly Shiny application. The platform is intended to make historical insights more accessible to clinical and statistical teams and support trial design optimization, sample-size planning, and go/no-go decisions.

The internship lasts 10–12 weeks and is based in Cambridge, Massachusetts. The intern must be able to relocate to the office and work 40 hours per week, Monday through Friday, for the full internship duration. The position offers mentoring and experience contributing to healthcare research and digital innovation.

Requirements

• Currently pursuing a master's or PhD degree in Biostatistics, Statistics, Computer Science, or a related field.
• Must be permanently authorized to work in the United States and not require employment visa sponsorship at the time of application or in the future.
• Must be enrolled in an accredited college or university throughout the internship.
• Must be able to relocate to the office location and work 40 hours per week, Monday through Friday, for the full internship duration.

Nice To Haves

• Machine learning experience.
• Experience with data visualization, including interactive plots.
• Experience with version control tools such as Git/GitHub.
• Experience with clinical trial data structures such as CDISC.

Responsibilities

• Explore the AD Placebo iDB, an internal database of historical AD clinical trial data.
• Develop predictive models for placebo response rates and variability across planned patient populations and study designs.
• Build an interactive Shiny application to predict placebo responses in future Phase 2/3 AD clinical trials.
• Document, validate, and deploy the predictive modeling framework and interactive platform.
• Support proactive trial design optimization, sample-size planning, and go/no-go decisions through the platform.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern