R&D Data Management Expert - Data and AI

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.

R&D Data Management Expert - Data and AI 

Job Posting Title

R&D Data Management Expert - Data and AI 

Job Description Summary

Develops, implements, and administers policies and procedures to ensure the quality and protection of organizational data, aligning with strategic priorities and regulatory requirements to minimize risk. Collaborates with leadership to define specific roles and responsibilities related to the organizations data assets, ensuring clarity in data stewardship. Develops and maintains rules and policies governing data management and access restrictions, promoting best practices in data governance. By fostering a culture of compliance and accountability, plays a critical role in safeguarding the organizations data integrity and security.

PURPOSE

Insight generation and business process optimization across R&D by ensuring internally generated data as well as externally sourced data are FAIR+Q (Findable, Accessible, Interoperable, Reusable, and of Quality). This is achieved, among other things, through the development and implementation of key data capabilities:

• Data and AI Catalog: Central location to find data assets, data models, AI Models, applications and related governance information


• Business Information Modeling: Connecting and describing data across domains


• Reference Data Capability: Providing standards for use in information models and workflows.


• Business Data Architecture: Charting data flow across business processes and systems


• Master Data Capability: Maintaining authoritative sources of key business data concepts such as project, product, sites etc. to gain a trusted, current view of these key data

The role will be responsible for the vision and delivery of the Data and AI Cataloging Capability while closely collaborating with Business Information Modeling, Business Data Architecture, Reference Data Standards, and other relevant data and AI capabilities. The domain scope of the role is all of R&D. The Data and AI Catalog expert acts as a business leader in initiatives involving the cataloguing of data, data models, AI models, governance policies and related information to allow humans and AI Agents access to information that is relevant for business workflows. The role collaborates closely with stakeholders across the organization to strengthen discoverability, understanding, ownership, quality, and usage conditions of R&D data assets.

STAKEHOLDERS

The role will interact and establish strong partnerships with

• Data producers, consumers, owners and stewards across R&D.  These could include lab and computational scientists, clinicians, statisticians, pharmaceutical and regulatory affairs professionals.


• Data architects, engineers, UI/UX engineers, product/platform/technology teams


• AI and ML scientists, engineers etc.


• Vendors and external contract staff


• Relevant Industry forums / consortia in the data and information space.

ROLES AND RESPONSIBILITIES

Data and AI Catalog Management (Pharma R&D Focus):Co-create and own the product vision, strategy, roadmap, rollout (resourcing, budgeting and delivery) and adoption (communication and metrics) of an R&D data and AI Model Catalog capability that aligns with the broader goals of the Pharmaceutical R&D team. This includes cross-domain search and discovery capabilities that enable scientists to find relevant data assets and reduce time to insight. Translate data cataloguing into business value by driving alignment between R&D data and AI model Catalog and key R&D business outcomes. Implement and manage specialized R&D data and AI Model catalog/s to maintain an inventory of a vast array of scientific data assets, from raw instrument outputs to curated datasets, data products, data models, AI models and services and governance policies.

• Partner with business and technical teams to create cohesive frameworks for access control, modeling, cross-domain discoverability, reusability for various analytics and AI use cases, and lifecycle management


• Enhance the catalog by ensuring integration with R&D systems, processes and AI services allowing scientists to quickly grasp the meaning, context, and reliability of data. Liaise with IT to troubleshoot technical issues, maintain server integrity, and integrations with other platforms and capabilities.


• Document and manage governance while taking into consideration the purpose and intended use of data, e.g. data sensitivity, privacy, GxP compliance, data lineage and data integrity. This is done in close collaboration with R&D Data Governance, Quality Assurance, Legal, Patents and Compliance, Regulatory Affairs, etc.


• Drive adoption and best practices across teams by providing tailored training on the use of the catalog for specific research needs. Monitor the usage and effectiveness of the data catalog.


• Establish feedback loops to capture unmet data needs and gaps in catalog coverage as well as improve data quality.


• Partner with business and technology teams responsible for business information modeling, business data architecture, master and reference data standards, other data and AI capabilities to enable seamless data operations across R&D

Strategic Leadership

• Influence without authority


• Operate collaboratively in a flat-hierarchy environment


• Advocate data capabilities usage across diverse R&D functions.


• Co-shape DSAI strategy for data and data science

WHO YOU ARE

• MS in Biological Sciences or MS Computer Science, Data Science, and Information Management preferably in a biomedical context.


• 10+ years in data catalog, metadata management and controlled vocabularies, related data and search capabilities in the biomedical domain. Product thinking would be a distinct bonus.


• Good understanding of pharmaceutical or life science R&D and the user base.


• Strong grasp of modern data governance and data quality, knowledge graphs, search/retrieval systems, AI and machine learning concepts, agentic workflows, DevOps, and modern data and AI stacks (e.g., AWS, Databricks, Collibra, Unity Catalog, Glue, SageMaker, MCP).


• Proven delivery of high-impact data and AI products/solutions for Pharma R&D - vision, approach, roadmap and delivery.


• Self-starter, independent yet collaborative, detail oriented, structured, process-oriented practitioner with reliable project management skills, able to influence a variety of stakeholders and manage ambiguity in a complex and changing environment.


• Strategic and conceptual thinker, effective communicator with a high learning agility, capable of translating across multiple domains and stakeholder archetypes.


• Excellent written and verbal communication skills in English.

Ever feel burnt out by bureaucracy? Us too. That’s why we’re changing the way we work— for higher productivity, faster innovation, and better results. We call it Dynamic Shared Ownership (DSO). Learn more about what DSO will mean for you in your new role here https://www.bayer.com/en/strategy/strategy

Bayer does not charge any fees whatsoever for recruitment process. Please do not entertain such demand for payment by any individuals / entities in connection with recruitment with any Bayer Group entity(ies) worldwide under any pretext.
 
Please don’t rely upon any unsolicited email from email addresses not ending with domain name “bayer.com” or job advertisements referring you to an email address that does not end with “bayer.com”.