Real-World Evidence Data Scientist

Sanofi; Berlin; Vor Ort; EUR 65.000 - 85.000; Vollzeit

Zusammenfassung

A global healthcare company in Berlin is looking for an RWE Data Scientist to manage and analyze real-world evidence projects. The ideal candidate will have a master's degree in a related field and expertise in machine learning and data analysis. Responsibilities include designing studies, translating requirements into specifications, and ensuring compliance with ethical standards. Competitive benefits and opportunities for innovation are provided.

Leistungen

Diversity and inclusion programs

Opportunities for skill development

Qualifikationen

• Experience in RWE, pharmaco-epidemiology, health outcomes research, and statistical methods.
• Proficiency in programming languages including R and Python.
• Experience with healthcare data sources like claims and EMRs.

Aufgaben

• Provide technical expertise for studies using real-world data.
• Translate business requirements into data analysis specifications.
• Communicate analysis results clearly to support decision-making.

Kenntnisse

Machine learning

Deep learning

NLP

Predictive modeling

Data analysis

Ausbildung

Master's degree in statistics, applied mathematics, or computer science

PhD preferred

Tools

R

Python

SQL

Snowflake

Jobbeschreibung

Job title :

In Sanofi General Medicines, we are dedicated to improving the day-to-day health of millions of patients around the world. Despite huge leaps forward in public health, many patients still don’t receive the care they need.

We are helping treat more patients today and enabling the science for better medicines tomorrow. We are transforming our business and engagement with customers to address chronic conditions like diabetes, cardiovascular disease, and transplant.

Leveraging our scale and expertise, we aim to maximize impact through healthcare partnerships, comprehensive treatment solutions, digital health models, data-driven personalization, and our Play to Win practices.

We harness innovation daily to stay ahead of our customers’ needs, providing support and hope to patients worldwide. Together, we are expanding our reach and elevating care standards for those battling chronic conditions globally.

The Real-World Data & Evidence Science (RWD&ES) team within General Medicines Medical acts as a strategic partner to solve business problems using real-world data. The team collaborates with medical, market access, health economics & value assessment (HEVA), and other cross-functional partners to lead RWE strategies—identifying data sources, developing strategies, and delivering impactful studies for stakeholders including patients, physicians, payers, and regulators. We are at the forefront of unlocking value from real-world data, translating it into insights to understand patient needs, influence medical practice, inform regulatory and access decisions, and improve health outcomes.

The RWE Data Scientist will manage and analyze RWE projects for the General Medicines portfolio, working closely with the RWE Data Science Analytics Lead to develop advanced analytics solutions. This role ensures high-quality, timely delivery of analyses aligned with the global RWD&ES roadmap, executing projects that leverage expertise in machine learning, deep learning, NLP, and predictive modeling. Collaboration with digital teams, global hubs, and analytics leads is essential to develop innovative solutions that support business growth.

We are an innovative global healthcare company focusing on immunology, diabetes, and transplant medicine. Our talented teams worldwide are committed to delivering a top-tier customer experience through digital, AI, and personal expertise. Our goal is to make a real impact on millions of patients' lives.

Main Responsibilities :

• Provide technical expertise for designing and delivering studies using real-world data with scientifically rigorous methods.
• Translate business requirements into data analysis specifications.
• Verify data source integrity and ensure compliance with data and ethical standards.
• Apply data science techniques such as machine learning, deep learning, NLP, and optimization to transform data into insights.
• Collaborate with internal and external experts to ensure analyses meet scientific standards.
• Communicate analysis results clearly to support decision-making.
• Adhere to best practices and documentation standards for data science processes.
• Stay updated with industry practices and emerging technologies like generative AI, testing innovative AI solutions.
• Maintain clear communication with team members, partners, and stakeholders about project progress and risks.
• Support medical gap analyses within the Global Evidence Generation Plans.
• Bring entrepreneurial energy, growth mindset, and passion for leveraging real-world data to improve health outcomes.

Education :

• Master’s degree in statistics, applied mathematics, computer science, or related fields; PhD preferred.

Experience :

• Expertise in RWE, pharmaco-epidemiology, health outcomes research, and statistical methods.
• Proficiency in R, Python, SQL; experience with Snowflake and other databases.
• Experience with healthcare data sources like claims, EMRs, registries, structured and unstructured data.
• Proven experience in advanced analytics, statistical modeling, causal inference, and machine learning techniques.
• Experience across multiple therapeutic areas, especially transplant, diabetes, or cardiovascular.

Soft skills :

• Sense of urgency, ownership, proactive attitude.
• Ability to communicate complex technical concepts to diverse audiences.
• Growth mindset for skill development.

Technical skills :

• Advanced programming and statistical skills, familiarity with Python, R, Scala, Snowflake, SQL, NoSQL.
• Expertise in supervised/unsupervised learning, deep learning, reinforcement learning, Bayesian statistics, optimization.
• Knowledge of RWE study designs and methodologies.
• Ability to translate technical language into clear communication and storytelling with data.
• Experience managing multiple projects and external vendors is preferred.

Languages :

• Fluent in spoken and written English.

At Sanofi, we are committed to diversity, equity, and inclusion. We offer equal opportunities regardless of background or identity. Join us to make a difference.