Lead Data Analyst

Lead Data Analyst

Location: Morristown, NJ

As a Lead Data Analyst within our Digital team, you will play a critical role in enabling high‑quality, trusted customer data across Sanofi's US commercial and enterprise ecosystem. Ready to push the limits of what's possible? Join Sanofi Digital! You will be a key contributor within the Customer Master Data team, supporting the delivery, monitoring, and continuous improvement of Customer 360 capabilities for the US market.

Working closely with the US Product Owner, GTMC stakeholders, Data Governance, Privacy, and Digital teams, you will focus on data analysis, data quality, and operational insights to ensure Customer MDM meets US business, regulatory, and analytical needs. Your work will directly support downstream systems such as CRM, analytics platforms, and identity solutions by ensuring accurate, consistent, and compliant customer data.

Join the digital engine driving Sanofi’s transformation – where AI, automation, and bold experimentation power faster science and smarter decisions. Here, you’ll help build the first biopharma company powered by AI at scale.

We’re an R&D‑driven, AI‑powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.

• Analyze US customer master data across data domains to ensure accuracy, completeness, consistency, and timeliness.
• Support the US Customer MDM product team by providing data‑driven insights to inform backlog prioritization, feature enhancements, and defect resolution.
• Perform data profiling, root cause analysis, and impact assessment for data quality issues affecting downstream systems such as CRM, analytics, USDF, and CIAM.
• Define, monitor, and report on US‑specific data quality KPIs, thresholds, and trends, partnering with Data Governance and Stewardship teams to drive remediation.
• Collaborate with US business stakeholders, GTMC teams, and country operations to understand customer data usage, pain points, and reporting needs.
• Translate business and operational questions into analytical requirements, queries, dashboards, and recurring data quality or operational reports.
• Support US market onboarding, enhancements, and releases by validating data readiness, conducting UAT data checks, and supporting go‑live activities.
• Partner closely with Data Engineers and Architects to validate source‑to‑target mappings, transformation logic, matching rules, and survivorship outcomes for US customer data.
• Ensure US Customer MDM data complies with local regulatory, privacy, and consent requirements by working with Privacy, Legal, and Compliance teams.
• Contribute to the implementation and adoption of US‑specific data standards, reference data, and stewardship processes.
• Support change management and adoption efforts by providing clear data insights, documentation, and guidance to business users and consuming systems.
• Identify opportunities for automation, reporting optimization, and advanced analytics to continuously improve Customer MDM data operations in the US market.

• Bachelor's degree in Information Science, Computer Science, Mathematics, Statistics, or a related quantitative discipline. Master’s degree preferred.
• 7+ years of experience in data analytics, data/database management, and data quality reporting within complex enterprise environments.
• Strong understanding of Customer Master Data Management (MDM), Customer 360 concepts, and data quality management, highly preferred within healthcare, pharmaceutical, or other regulated industries.
• Proven hands‑on experience analyzing large, complex datasets using SQL (Snowflake experience and working knowledge of Python preferred).
• Experience using at least one BI/reporting tool such as Power BI, Qlik Sense, or Tableau to deliver clear insights to business and technical stakeholders.
• Solid knowledge of data modelling and data warehousing principles, including data cleansing,…