Job
- Level
- Lead
- Job Field
- Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Salary
- 109.800 to 138.500€ gross/year
- Location
- Berlin
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will shape data science projects from design through complex analyses to insights communication, and develop innovative AI-driven solutions for evidence-based decision-making.
Job Technologies
Your role in the team
- Lead and shape high-impact data science initiatives across the full analytics lifecycle, from study design and data feasibility assessments to advanced analyses, interpretation, and communication of insights using real-world data, statistical methods, machine learning, and AI.
- Design and implement innovative analytical solutions that advance real-world evidence generation, strengthen scientific rigor, and support product commercialization, lifecycle management, and healthcare decision-making.
- Build and scale AI-enabled analytical capabilities by developing vendor-agnostic AI agent toolkits, reusable machine learning components, and intelligent workflows that accelerate evidence generation.
- Drive the responsible adoption of AI by establishing practical validation approaches, governance principles, and quality standards that align with scientific, ethical, and regulatory expectations.
- Develop robust evaluation frameworks for AI-powered analytical workflows, ensuring transparency, traceability, reliability, and appropriate risk mitigation when working with complex real-world data.
- Act as a trusted scientific and technical leader, providing guidance, mentorship, and coaching to colleagues while fostering a culture of collaboration, continuous learning, and innovation.
- Partner closely with cross-functional teams, including Global Medical & Evidence, Product Teams, R&D Data Science, Clinical Development, HEOR, Market Access, and external collaborators, to translate business and scientific questions into actionable evidence and insights.
- Contribute to the strategic growth of RWDS&AI by advancing data science methodologies, AI/ML capabilities, infrastructure priorities, and best practices, while representing the organization through scientific collaborations, publications, and conference presentations.
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Our expectations of you
Qualifications
- You hold a PhD (preferred) or MSc in Data Science, Computational Science, (Bio-)Informatics, Mathematics, Statistics, Physics, Engineering, Epidemiology, Econometrics, Machine Learning, or a related discipline.
- You have a proven track record of leading complex analytical projects, influencing strategic decisions, and supporting the development of technical teams.
- You bring deep expertise in Statistical Analysis, including causal inference, advanced adjustment methods, sensitivity analyses, and the development of scientifically robust analytical approaches aligned with regulatory expectations.
- You have strong capabilities in Machine Learning, AI, and Software Engineering, including the development of reusable models, pipelines, AI-enabled workflows, and production-ready analytical solutions that create business value.
- You possess hands-on expertise in Data Science Infrastructure, Data Modeling, Ontologies, and Programming, with advanced proficiency in Python and/or R, SQL, modern analytical platforms, reproducible workflows, and standardized data models such as OMOP CDM.
- You are a collaborative communicator with strong analytical thinking, stakeholder management, problem-solving, adaptability, and innovation skills, and you communicate fluently in English, both written and spoken.
Experience
- You bring extensive professional experience in Data Science, Advanced Analytics, or a related field. Experience within healthcare, life sciences, or the pharmaceutical industry is highly valued.
- You are an expert in Real-World Data (RWD) and have experience designing scalable analytical solutions, defining data models, assessing data feasibility, and selecting appropriate data sources to answer complex research questions.
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What we offer
- We ensure your financial stability with a competitive salary between €109,800 and €138,500 per year (full-time) plus a variable component and a global equity-based cash plan.
- Your compensation is based on your qualifications, skills, and professional experience.
- Whether it's hybrid work models or part-time arrangements: Whenever it is possible, you will have the flexibility to work how, when and where it is best for you.
- Your family is a top priority. We offer loving company daycare centers at multiple locations, support in finding childcare, time off for the care of elderly or dependent family members, summer camps for children, and much more.
- We support your professional growth by providing access to learning and development opportunities, training programs through the Bayer Learning Academy, development dialogues, as well as coaching and mentoring programs.
- We promote health awareness and opportunities for self-care through various measures, such as free health checks with the company doctor.
- We embrace diversity by providing an inclusive work environment in which you are welcomed, supported, and encouraged to bring your whole self to work.
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Benefits
Work-Life-Integration
Health, Fitness & Fun
Higher Take-Home Pay
Topics You Will Work On
Job Locations
About Your Employer
Bayer AG
Bayer AG is a globally active company with core competencies in the life science fields of health and nutrition. We develop our products and services for the benefit of people and the planet, and are committed to addressing the global challenges of a constantly growing and aging world population.
Description
- Company Type
- Established Company
- Working Model
- Full Remote, Hybrid, Onsite
- Industry
- Pharmaceutical Sector, Chemical Industry, Biotech
Senior Lead Data Scientist
- Salary
- 109.800 to 138.500€ gross/yearEstimated net salary based on the gross salary in the job ad using tax class I.63.137 to 78.447 € net/year · Tax class I
- Location
- Berlin
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
- English Only
- English only required
