Compensation DataThe base salary range for this position is $140,000 to $222,000. The position may be eligible for a role specific discretionary bonus, relocation, and/or other compensation elements. We continuously review market data and may adjust salary ranges as needed in the future. Actual compensation will be based on job-related factors such as skills, experience, and qualifications, and other factors permitted by law. For an overview of our benefits please click here .
DescriptionThe AD, Data Governance leads governance and operational oversight of our de-identified patient data and platform, ensuring all datasets meet privacy, compliance, and analytic readiness standards. This role manages data ingestion and validation workflows, oversees schema governance and secure data access and controls, and serves as a key liaison between analytics, IT, privacy, and external data partners. This includes coordinating and implementing RRD (Re-Identification Risk Determination) assessments and applying any resulting required remediations. The role also guides use case reviews and the approval process to ensure that any access to de-identified patient data meets governance, privacy, and compliance requirements, while enabling timely, trusted analytics for our brands.
- This role is based on-site at our Ridgefield, CT location with hybrid flexibility of 2-3 days per week on-site.
Duties & Responsibilities- Lead governance and operational oversight of de-identified patient data and platforms, ensuring all datasets meet privacy, compliance, quality, and analytic-readiness standards.
- Manage data ingestion, validation, and quality workflows, including schema governance, metadata standards, and controls for secure data access across internal and external stakeholders.
- Coordinate and support RRD (Re-Identification Risk Determination) assessments, ensuring required remediations are implemented and continuously monitored.
- Serve as the central liaison between analytics, IT, privacy, compliance, and external data partners, ensuring accuracy, timeliness, and trustworthiness of de-identified patient data.
- Guide and administer use-case review and approval processes to ensure data access aligns with governance, privacy, and regulatory requirements while enabling timely analytics for business needs.
- Mange linked data processes within our de-identified patient data warehouse.
Requirements- Bachelor's degree from an accredited institution and seven (7) years of related pharmaceutical industry experience with five (5) years of secondary data experience in sales operations, sales/marketing analytics, market research, managed markets or business Analysis; OR
- Master's degree from an accredited institution and five (5) years of related pharmaceutical industry experience with five (5) years of secondary data experience in sales operations, sales/marketing analytics, market research, managed markets or business Analysis.
- Excellent communication skills both written and verbal.
- Demonstrated experience in leading cross functional project teams and influencing upward.
- Ability to manage a large vendor and hold them accountable for data accuracy and meeting deliverable.
- Prior budgeting experience helpful.
- More than six (6) years project management experience
- Identifies emerging pharmaceutical industry data sources, evaluates their effectiveness in business practices the recommends its use across Prescription Medicines.
- Ensures best practices of third-party data usage.
- Accountable for assisting in negotiating third party data vendor pricing in support of sales analytics, managed markets, market research and other various analytical departments.
Desired Experience, Skills and Abilities:
- Working knowledge of third party sub-national data sets used to support sales and marketing. Previous work experience in targeting, call planning, sales and/or marketing analytics is preferred.
- Working knowledge of third party de-identified patient datasets.
- Working knowledge of database architecture, access & controls, and monitoring.
- Experience with data tokenization processes.
