Advisor R&D: Data Standards and Strategy

Your Role:

Develops, implements, and maintains R&D data model, governance frameworks and standards for electronic data, ensuring data quality, accessibility, and usability for advanced analytics and AI/ML initiatives. This role will be formative in establishing new ways of working with Elanco R&D data across functional areas, requiring significant leadership and strategic input.

Your Responsibilities:

Lead the design, implementation, and maintenance of the electronic data governance program, including establishing frameworks, policies, and guidelines, ensuring alignment with Elancos values, corporate policies, regulatory requirements, and the needs of AI/ML initiatives.

Drive the design, implementation, and operationalization of metadata management strategies, including data catalogs and data dictionaries, to ensure consistent metadata, lineage, and quality for use in platforms like Databricks and Power BI.

Champion cross-functional collaboration with business stakeholders (R&D, IT, and Quality Assurance) to strategically align data governance objectives with practical data needs, ensuring seamless integration with existing data management procedures and proactively identifying new ways of working suitable for advanced analytics and AI/ML.

Lead the development and delivery of comprehensive training materials to promote data literacy and foster a data-driven culture across the organization, with a focus on enabling data utilization for AI/ML.

Oversee the implementation, tracking, and strategic direction of data quality monitoring and cleaning processes, including establishing and refining metrics/KPIs to proactively identify, monitor, and address data quality, accessibility, bias mitigation, and overall program maturity, reporting performance and risks to leadership.

What You Need to Succeed (minimum qualifications):

Education : Bachelors in data science or similar.

Experience: 8+ years of experience in data governance, AI/ML governance, data product management, or risk/compliance in data-centric organizations

Ability to translate between technical requirements and stakeholder business needs.

What will give you a competitive edge (preferred qualifications):

Data experience in animal health or pharmaceutical industry, particularly understanding types of data and how they are used in these industries

Strong understanding of data governance tools, frameworks and AI risk management models.

Familiarity with regulations including GDPR, CCPA, and emerging AI legislation.

Hands-on experience with data and AI tooling (ex. Databricks, Power BI, etc).

Familiarity with metadata, data lineage, access controls, and master data strategies.

Proven leadership experience driving cross-functional influence across technical stakeholders and business leaders.