The Senior Manager, R&D Data Literacy & Monetization drives the strategic use of enterprise R&D data assets by transforming governed datasets into reusable data products that deliver measurable business value. This role sits within the R&D Data Governance organization and serves as a critical bridge between business stakeholders, data platform teams, and governance functions to enable data-driven decision-making, advanced analytics, and AI initiatives. In addition, the role champions data literacy, adoption, and a culture of trusted data usage, ensuring that R&D data is not only well-governed but actively leveraged to generate insights, improve efficiency, and drive innovation.
This role enables the organization to unlock the full value of its R&D data by increasing reuse of governed datasets, reducing duplication of analytics efforts, supporting advanced analytics and AI-driven initiatives, strengthening data-driven decision-making, and demonstrating measurable returns on data investments.?
Essential Functions of the job:
Identify High-Value Data Assets
Partner with R&D stakeholders during use case intake and prioritization to identify high-value data opportunities
Evaluate datasets based on business impact, reusability, and analytics/AI potential
Develop and apply a data asset value framework to prioritize datasets for productization
Create Reusable Data Products
Collaborate with engineering, modeling, and governance teams to build scalable, reusable data products that align with Bronze ? Silver ? Gold medallion architecture
Ensure datasets are governed, standardized, and enriched with business logic, metadata, and quality controls
Enable delivery via analytics-ready datasets, APIs, and AI/ML-ready assets
Publish and promote data products via data catalog and marketplace
Enable Internal Value Creation
Drive cross-functional data reuse and insights across R&D
Enable use cases such as benchmarking, standardized reporting, and AI-driven analytics
Ensure secure and compliant data access in partnership with governance and compliance teams
Promote adoption through governed platforms and standardized processes
Data Governance & Consumption Enablement
Ensure all data products meet standards for data quality, metadata, lineage, and stewardship
Maintain compliance with privacy, regulatory, and security requirements
Define and support data catalog and marketplace strategy
Enable self-service access, provisioning workflows, and documentation
Track and drive data product adoption and usage
Value Realization & Impact Measurement
Define and track KPIs for data product adoption and value realization
Measure impact across Data reuse and adoption, Operational efficiency, Cost savings, Analytics and AI enablement
Develop dashboards and executive reporting on data value
Data Literacy & Culture Enablement
Develop training and guidance to improve data literacy and adoption
Promote data stewardship, metadata usage, and governance practices
Foster a culture of data trust, quality, and informed decision-making
Cross-Functional Collaboration
R&D Business Stakeholders
Data Governance & Stewardship
Data Engineering & Modeling
Analytics & AI/ML Teams
Legal, Compliance & Privacy
Supervisory Responsibilities:? ??
Qualifications & Skills
7+ years of experience in data strategy, data governance, analytics, or data product management
Experience in biotech, pharmaceutical, or healthcare R&D environments
Strong understanding of Data governance frameworks, Data product lifecycle, Data privacy, security, and regulatory requirements
Experience with modern data platforms and analytics ecosystems (e.g., Databricks)
Hands-on experience with metadata management and data stewardship tools (e.g., Informatica CDGC/CDQ, Collibra, Reltio or similar MDM platforms)
Familiarity with medallion architecture (Bronze ? Silver ? Gold)
Experience working with clinical, safety, or R&D analytics data
Experience developing data literacy programs or training initiatives within R&D organizations
Strong ability to derive actionable insights from large datasets and translate them into business value
Understanding of how R&D data drives operational insights, decision-making, and enterprise value
Basic understanding of financial concepts related to data value realization and monetization
Core Competencies
Strong stakeholder engagement and leadership
Strategic thinking and problem-solving
Ability to balance scientific, operational, and compliance needs
Excellent communication and executive presentation skills
Commitment to data quality, governance, and trust
Education
Bachelor's degree in Life Sciences, Information Systems, Data Management, or related field
Advanced degree (e.g., MS, MBA) in data science, life sciences, or business preferred
Technical Skills
Proficiency in Microsoft Office Suite (Outlook, Word, Excel, PowerPoint, Project)
Strong knowledge of data architecture, data lakes, ETL processes, and database management systems.
Ability to conduct statistical analyses and interpret findings relevant to R&D and business operations.
Familiarity with machine learning concepts and how they can be applied to R&D datasets to derive insights.
Travel :?
BeOne Global Competencies:
When we exhibit our values of Patients First, Collaborative Spirit, Bold Ingenuity and Driving Excellence, through our twelve global competencies below, we help get more affordable medicines to more patients around the world.
Fosters Teamwork
Provides and Solicits Honest and Actionable Feedback
Self-Awareness
Acts Inclusively
Demonstrates Initiative
Entrepreneurial Mindset
Continuous Learning
Embraces Change
Results-Oriented
Analytical Thinking/Data Analysis
Financial Excellence
Communicates with Clarity
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.