Senior Director, Head of Data Governance & Compliance

GSK•Upper Providence Township, PA

About The Position

If you believe data governance should accelerate innovation - not slow it down - this role is for you. We’re looking for a transformational leader to modernize how governance is designed, delivered, and experienced across R&D. Think policy-as-code, responsible AI ready controls, and federated ownership embedded in real workflows. Your mission is to ensure our data is trusted, compliant, and reusable by first intent, so scientists and product teams can move faster with confidence.

Requirements

Bachelor’s/master’s in computer science, Data Management, Mathematics, Statistics, Biostatistics, or related fields.
5+ yrs of transforming governance functions with innovative solutions that create competitive edge, from automation and policy-as-code to scalable reuse practices.
10+ yrs operating in ambiguous, fastmoving environments where you’ve had to create the playbook, align stakeholders, and deliver measurable outcomes.
Proven leadership in data governance/data management and complex R&D programs; fluency in regulatory frameworks (GxP, GDPR, HIPAA).
Industry exposure to responsible AI and AI/ML lifecycle management; familiarity with Python/R/SQL and modern data platforms; governance certifications (DAMA/DMBOK, DCAM, EDM Council) appreciated.

Nice To Haves

Proficiency in data science techniques, including data analysis, machine learning, and statistical modeling.
Expertise in programming languages such as Python, R, SQL, and C++.
Experience with data management tools and platforms (e.g., Hadoop, Spark, SQL databases).
Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud).
Ability to create and interpret data visualizations using tools like Tableau, Power BI, and D3.js.

Responsibilities

Set the strategy for R&D wide governance and compliance framework that directly underpins R&D digital transformation, grounded in real regulatory rigor (GxP, GDPR, HIPAA) and designed to enable innovation, not gate it.
Build and modernize the governance function: standards, metadata/master data, lineage, and data quality, delivered through a federated model that empowers domains while keeping us interoperable.
Embed governance in the flow of work by partnering with business and tech teams, making controls seamless, and measurable, across the lifecycle.
Operationalize policy‑as‑code and adaptive compliance to reduce manual effort and accelerate decisions.
Advance responsible AI governance (bias, explainability, monitoring) and pilot agentic AI to automate stewardship where it makes sense.
Champion a reuse culture so value creation and interoperability become default behaviors across R&D.
Measure impact with clear KPIs for governance effectiveness, data quality, compliance, and engagement, continuously iterating based on analytics and feedback.

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