Director, R&D Data Enablement/Data Products

BeOne continues to grow at a rapid pace with challenging and exciting opportunities for experienced professionals. When considering candidates, we look for scientific and business professionals who are highly motivated, collaborative, and most importantly, share our passionate interest in fighting cancer.

As Director of R&D Data Enablement / Data Products, you will lead the strategy and execution of building and scaling R&D data foundations and data products that transform data into a strategic asset. You will be responsible for delivering high-quality, reusable, and governed cross-domain operational data foundations, as well as domain-specific data products that accelerate scientific outcomes, fuel AI/ML ambitions, and deliver business value across the Pharma R&D value chain. By collaborating with stakeholders across Research, Clinical, Safety, Regulatory, Portfolio & Project Management and other R&D functions, you will ensure data is discoverable, interoperable, and analytics-ready, enabling smarter and faster decisions that advance scientific breakthroughs and patient outcomes.

Strategy & Roadmap

• Define and lead the multi-year strategy for R&D data foundations and data products, aligned with R&D priorities, digital/AI ambitions, and enterprise data strategy.

• Establish and communicate a clear roadmap for delivering cross-domain operational data layers (e.g., studies, sites, patients, compounds, products) and domain-specific data products.

• Drive alignment with business leadership by linking data foundations to measurable outcomes (e.g., trial efficiency, accelerated submissions, improved patient safety).

Data Foundations & Architecture

• Oversee design and implementation of scalable R&D data foundations leveraging medallion/ lakehouse architecture principles.

• Partner with data engineering to build shared “golden / analytics ready” data products and reusable domain-specific data layers.

• Ensure harmonization of external and internal standards (CDISC, HL7/FHIR, MedDRA, internally defined ontologies / standards) embedding FAIR data principles.

Data Product Development

• Build a portfolio of high-value data products that address critical R&D use cases (e.g., portfolio insights, clinical trial optimization, regulatory intelligence).

• Establish best practices for data product design, lifecycle management, SLAs, and adoption metrics.

• Partner with business owners to embed data products into decision-making workflows, ensuring measurable impact and user adoption.

AI & Advanced Analytics Enablement

• Deliver high-quality, analytics-ready datasets and features that enable AI/ML use cases across the R&D lifecycle.

• Partner with AI/ML and data science teams to accelerate model development by ensuring data foundations are curated, contextualized, and compliant.

• Champion innovation by piloting AI-enabled data products and scaling successful solutions.

Cross-Functional Leadership & Engagement

• Lead and mentor a multidisciplinary team including Business/Data Analysts, Data Stewards, and Data Modelers to deliver on the data enablement goals.

• Collaborate with domain leaders, governance, and platform teams to ensure seamless integration of data foundations with governance, access, and compliance frameworks.

• Act as a trusted advisor to senior R&D stakeholders, translating scientific and operational needs into scalable data solutions.

• Lead forums and communities of practice to drive a culture of data product thinking and self-service adoption.

Value Realization & Continuous Improvement

• Define and track key metrics for adoption, business impact, and ROI (e.g., reduced cycle times, cost savings, improved decision confidence).

• Establish feedback loops to enhance usability, quality, and scalability of data products.

• Continuously assess emerging technologies and practices to advance the organization’s data enablement maturity.

Supervisory Responsibilities:  

• Yes

Computer Skills:

• Microsoft Applications (Outlook, Word, Excel, PowerPoint, Project)

Qualifications:   

• Bachelor’s degree in Life Sciences, Data Management, Computer Science, or related field; Master’s or PhD preferred.

• 10+ years of experience in data management, data products, or analytics enablement, with significant experience in Pharma R&D.

• Proven track record of designing and delivering scalable dat