Statistical Innovation Lead m​/f​/d

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us.

If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

At Bayer, we are committed to driving innovation in clinical statistics and analytics. As a Statistical Innovation Lead, you will leverage advanced statistical methodologies to optimize clinical trial designs and data analytics across various stages of drug development. You will play a pivotal role in innovating through novel study designs, advanced modelling, and simulation techniques, including Bayesian methods and predictive analytics.

Your work will directly influence decision‑making processes and support quantitative decision‑making during drug development and life‑cycle management of Bayer products.

• Serve as a member of the expertise hub, supporting Study/Project Statisticians and clinical project teams in implementing innovative trial designs and advanced statistical methodologies;
• Address complex challenges in drug development and life‑cycle management using advanced modelling and simulation techniques, including Bayesian methods and predictive analytics;
• Apply innovative approaches to utilize various data sources, enhancing data insights and gaining efficiencies for agile data‑driven decision‑making;
• Drive the development and implementation of novel study designs, including adaptive and Bayesian model‑based designs, and advanced data analytic tools using state‑of‑the‑art statistical methodologies;
• Provide innovative statistical and methodological approaches to optimize clinical trial designs, leveraging AI, machine learning, and advanced statistical methods to support real‑world evidence and personalized medicine strategies;
• Represent the Statistical Innovation group to internal and external stakeholders regarding statistical and innovative aspects of clinical development programs and products;
• Maintain an external network through active conference participation and collaboration with academic institutions, industry groups, and Health Authorities to stay at the forefront of statistical innovation;
• Provide training to Statisticians, clinical project teams, and internal stakeholders on advanced statistical methods and novel study designs for knowledge sharing and large‑scale adoption.

• University degree (PhD preferred) in Biostatistics, Statistics, Mathematics, or a related field;
• At least eight years of experience as a Statistician or in an applied quantitative methods role, with significant time in pharma, biotech, or a similar sector;
• High level of expertise in applying innovative statistical methodologies to a broad range of study designs, including adaptive designs and advanced modelling techniques, with working knowledge of Bayesian methods;
• Embrace and role model the VACC (Visionary/Architect/Catalyst/Coach) behaviours in leadership, with mentoring and coaching capabilities across diverse cultural environments;
• Outstanding interpersonal, leadership, and communication skills, with fluent English and strong presentation skills;
• Ability to work independently and collaboratively as required;
• Thorough knowledge of the pharmaceutical industry and understanding of the clinical drug development process, including regulatory requirements governing clinical trial data;
• Excellent knowledge of statistical programming languages (SAS, R, Python) and Bayesian software (BUGS, JAGS, Stan), including experience building RShiny applications;
• Demonstrated leadership skills in leading teams of Statisticians and representatives from other functional clusters;
• Broad expertise in multiple fields relevant to clinical development;
• High affinity for internal and external…