Benefit Risk Management Center of Excellence Data Scientist

Benefit Risk Management Center of Excellence Data Scientist provides scientific and analytical solutions for Benefit Risk Management (BRM), supporting Global Safety Leaders (GSL), Center of Excellence (CoE) and Medical Device Safety (MDS) in the use of data-driven tools and data sources. The BRM CoE Data Scientist Leads the development of innovative solutions using novel technologies which facilitate the analyses required to provide answers to medical questions and meet regulatory requirements. Has a deep knowledge of analytical/data science methods, and tools, which enables identification of business needs and the capability to choose and implement the right solutions. Delivers solutions which increase the efficiency of data science and data analytics in BRM, combining data from different sources, and facilitating the generation of new insights which support the ongoing benefit risk management of Bayer products. Has a good understanding of data science, statistics, machine learning, and Artificial Intelligence (AI) including modern LLM systems, is able to evaluate AI use cases for BRM, assess feasibility, and incorporate these technologies into operational systems. Scope (global, regional or local): global.

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• Lead Data Science and Analytics projects, working closely with colleagues in multiple BRM Therapeutic Groups and across the organization (Regulatory Affairs, Clinical Development, and IT).
  
• Serve as a catalyst and drive the development of BRM data science and analysis/retrieval strategies, and data visualization solutions that benefit the whole BRM organization.
  
• Drive standardization of processes and develop standardized best practice solutions for recurring data science and analysis tasks across BRM.
  
• Lead sub-teams working on specific Data Science and Analytics projects or ideas, coordinating with BRM team members, project managers, and peers across CMO and IT.
  
• Support PV and BRM transition to utilize novel technologies to advance analytical tools and data sources.
  
• Experiment with data science prototypes and develop into to operational, validated end to end solutions.
  
• Fully utilise business intelligence capabilities to incorporate new and innovative solutions into templates/workbooks (e.g., in Spotfire) to increase the efficiency of analytics in BRM.
  
• Identify and implement AI-driven solutions to automate pharmacovigilance workflows, enhance signal detection, and optimize benefit-risk assessments.
  
• Collaborate with cross-functional teams to integrate generative AI and large language models (LLMs) into BRM platforms.
  
• Design robust experiments and monitoring to ensure AI solutions are safe, reliable, and valuable.
  

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• Present new ideas to peers and senior BRM leadership and other stakeholders to get buy-in and set up new projects with the IT platform.
  
• Present new solutions and act as advanced trainer to BRM on Data Science and analytical tool use, database content and query strategies.
  
• Coach the GSLs on Argus database content by having a deep knowledge of Argus data, process rules, and develop a new way of aligning PV product data with regulatory systems for easier maintenance.
  
• Combine data sources to automatically perform calculations relating to frequencies, exposures, and reporting rates.
  
• Generate the data including aggregate summary tabulations, descriptive statistics, trend analysis, outliers, and correlations, and use this data to automatically populate report templates.
  
• Ensure compliance with computer system validation procedures and create documents such as user requirements specifications, system specifications and user acceptance test scripts, to support implementation of new GxP systems and change requests.
  
• Data architect/expert for BRM analytical platforms e.g., DAVIS.
  
• Act as deputy to Data Science and Analytics Lead regarding process manager to PV tools and BRM representative in forums such as change committees, digital initiatives, and digital councils.
  
• Explore opportunities to enhance BRM capabilities using emerging technologies, including automation and intelligent data processing.
  
• Collaborate with internal stakeholders to assess the feasibility of applying AI-supported tools to streamline benefit-risk processes.
  
• Design and build prototype solutions that apply advanced analytics and/or AI-supported methods to address BRM challenges.
  
• Translate scientific and safety-related use cases into operational tools, ensuring usability and compliance with regulatory standards.
  
• Lead the implementation of projects that apply automation and intelligent data processing to enhance BRM processes.
  

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• Master's degree and long-term years of relevant professional experience is required, Master in Information Systems or computer science preferred.
  
• Professional experience in a field of natural sciences, such as medicine/human biology/pharmaceuticals or medical information/ documentation management strongly preferred.
  
• Several years experience in pharmacovigilance or pharmaceutical industry preferred.
  
• Expert understanding of technology landscape and data pipeline as well as proven ability in defining technical requirements for business and a strong understanding of the use and consumption of data are required.
  
• Advanced experience and confidence in working with databases and data analysis tools (e.g., Spotfire, Excel).
  
• Excellent understanding of retrieval processes and knowledge of database query language for generating outputs (e.g., SQL).
  
• Knowledge of the activities and processes involved in pharmacovigilance and the rules and regulations associated with this (GxP guidelines), as well as knowledge of periodic safety reporting (e.g., PBRER, DSUR) to the responsible supervisory authorities (e.g., EMA, FDA) and knowledge of medical classification systems (e.g., MedDRA coding) are strongly preferred.
  
• Strong technical expertise in managing tools, data queries and data processing are required.
  
• Demonstrated ability to learn new databases and data analysis tools.
  
• Proven ability to take on new challenges, understand and analyze complex problems, and lead in developing and rolling out solutions.
  
• Excellent communication and presentation skills for organized information exchange on specific topics between the various working groups.
  
• Project management skills and proven ability to lead work groups/teams to define requirements and implement solutions.
  
• Very good written and spoken knowledge of English.
  
• Knowledge of data science models, methodologies and tools (Python and R) required.
  
• Ability to think strategically and ensure focus on most value adding tasks.
  
• Familiarity with AI and machine learning concepts, with experience applying them in scientific or safety-related contexts.
  
• Ability to evaluate and adopt AI-supported tools that enhance pharmacovigilance and benefit-risk management processes.
  
• Experience in Retrieval Augmented Generation (RAG), fine tuning, LLM evaluation, Responsible AI, and ML operations (MLOps).
  

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.

Competitive compensation package consisting of an attractive base salary and annual company bonus.

Individual bonus can also be granted for top Talent Impact.

28 days annual leave plus bank holidays.

Private Healthcare, generous pension scheme and Life Insurance.

Wellness programs and support.

Employee discount scheme.

International career possibilities.

Flexible and Hybrid working.

Help with home office equipment.

Volunteering days.

Support for professional growth in a wide range of learning and development opportunities.

We welcome and embrace diversity providing an inclusive working environment.

• 
  
• Competitive compensation package consisting of an attractive base salary and annual company bonus.
  
• Individual bonus can also be granted for top Talent Impact.
  
• 28 days annual leave plus bank holidays.
  
• Private Healthcare, generous pension scheme and Life Insurance.
  
• Wellness programs and support.
  
• Employee discount scheme.
  
• International career possibilities.
  
• Flexible and Hybrid working.
  
• Help with home office equipment.
  
• Volunteering days.
  
• Support for professional growth in a wide range of learning and development opportunities.
  
• We welcome and embrace diversity providing an inclusive working environment.