Principal Scientist & CMC Statistician — Drug Development

Sanofi; Framingham (MA); On-site; USD 140,000 - 190,000; Full time

Job summary

Sanofi in Framingham, MA is seeking a Principal Scientist - CMC Statistician to provide statistical support for process development, analytical methods, and formulation development across multiple CMC sites worldwide.

You will design experiments, analyze data using R, SAS, Python, and JMP, prepare reports for Health Authorities, and mentor teams on statistical methodology while advancing state-of-the-art techniques.

Qualifications

• PhD or Master in statistics or related field.
• 3+ years (PhD) or 6+ years (Master) of statistical work in CMC/industrial settings.
• Proficient in R or JMP; SAS or Python a plus; strong reporting skills.

Responsibilities

• Provide statistical support to CMC scientists for process development and QbD.
• Deliver experimental design, data analysis, and interpretation of results.
• Perform analyses using R, SAS, Python, JMP, SIMCA, MODDE, and related tools.
• Prepare statistical reports and presentations for project teams and regulators.
• Design and analyze studies intended for Health Authorities and filings.
• Write study reports complying with internal policies and regulatory guidelines.
• Serve as CMC statistics contact between statistics group and related functions.
• Promote statistical thinking and train laboratories in methodologies.

Skills

Statistical modeling

DoE

Multivariate analysis

Data analysis

Scientific communication

Education

PhD in Statistics or related field

Master's degree in Statistics/CMC/Applied Math/Data Science

Tools

R

SAS

Python

JMP

SIMCA

MODDE

Job description

Sanofi in Framingham, MA is seeking a Principal Scientist - CMC Statistician to provide statistical support for process development, analytical methods, and formulation development across multiple CMC sites worldwide.

You will design experiments, analyze data using R, SAS, Python, and JMP, prepare reports for Health Authorities, and mentor teams on statistical methodology while advancing state-of-the-art techniques.