Scientific Data Analyst

Job Summary

Scientific Data Analyst within the Vaccines Biostatistical Sciences team. Leverage programming and AI/ML to analyze clinical trials data, build end‑to‑end evidence pipelines, and drive modern data methods across studies.

Responsibilities

• Perform clinical trial data analyses – conduct exploratory and confirmatory analyses on SDTM and ADaM datasets, collaborating with biostatisticians to deliver high‑quality, reproducible, submission‑ready outputs (tables, listings, figures).
• Champion modern programming practices – transition from SAS to open‑source languages (R, Python), promote version control, code review, modular programming, and reproducible research frameworks.
• Leverage AI & Machine Learning to augment statistical programming – explore and implement AI‑powered tools (LLMs, code generation, automated QC) to accelerate and enhance programming workflows.
• Develop and maintain analytical tools – build reusable packages, pipelines, and automation frameworks that improve efficiency, standardization, and scalability of analyses across studies.
• Collaborate closely with biostatisticians – translate SAPs into robust code, contribute to analytical approaches, and provide programming expertise in cross‑functional teams.
• Contribute to the evolution of the statistical programming practice – participate in defining new standards, tools, and methodologies; act as an internal advocate for data‑science innovation.
• Stay at the forefront of emerging technologies – monitor new AI/ML tools, open‑source developments, and industry trends (Pharmaverse, Posit/RStudio ecosystem) to bring forward‑thinking solutions into the organization.

Qualifications

Experience: Exposure to real‑world data projects through academic research, internships in pharma, biotech, CRO or healthcare analytics, Kaggle competitions, hackathons, or open‑source contributions.

Technical skills: Strong proficiency in Python and/or R for data manipulation, visualization, reproducible workflows, and data analysis.

Soft skills: Demonstrated leadership, interpersonal skills for multicultural teamwork, ability to embrace and lead change, curiosity to innovate, and a desire to improve team practices.

Digital acumen: AI/ML enthusiast, automation mindset, self‑learner.

Education: Master’s degree in Statistics, Data Sciences/Machine Learning, applied mathematics, or engineering with quantitative specialization. Preferred coursework or projects involving healthcare, life sciences, or clinical research data.

Languages: Fluent in English; additional languages are a plus.

Benefits

• Fixed salary over 12 months with group variable compensation based on Sanofi Group results.
• Comprehensive health insurance, extended maternity/parental leave (18/14 weeks), support for illness, teleconsultation and second medical opinion covered.
• Work‑life balance: 31 days paid leave + RTT, remote work up to 2 days per week.
• Public transport coverage up to 80%.
• Group savings and retirement plans with employer matching.
• Professional development: internal and international mobility, learning and development opportunities.
• Peer‑to‑peer recognition platforms, service exchanges (carpooling, home exchanges), CSE benefits.

Salary

€38560,00 – €51413 per year (final compensation based on experience, skills, location, and other factors).

EEO Statement

Sanofi is an equal opportunity employer, providing equal opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.