Associate Director, Data and Analytics

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Madrigal is a biopharmaceutical company focused on delivering novel therapeutics for metabolic dysfunction-associated steatohepatitis (MASH), a serious liver disease that can progress to cirrhosis, liver failure, need for liver transplantation and premature mortality. Every member of our Madrigal team is connected by our shared purpose: leading the fight against MASH.

Madrigal’s medication, Rezdiffra (resmetirom), is a once-daily, oral, liver-directed THR-β agonist designed to target key underlying causes of MASH. Rezdiffra is the first and only medication approved by both the FDA and European Commission for the treatment of MASH with moderate to advanced fibrosis (F2 to F3). An ongoing Phase 3 outcomes trial is evaluating Rezdiffra for the treatment of compensated MASH cirrhosis (F4c).

Our success is driven by our people. We are building a dynamic, inclusive, and high-performing culture that values scientific excellence, operational rigor, and collaboration. To support our continued growth, we are strengthening our workforce strategy to ensure we have the right talent, at the right time, in the right way.

Reporting to Executive Director of Data and Analytics as Associate Director of Data and Analytics, you will play a critical leadership role within the Data & Analytics organization, supporting Corporate, Finance, and Supply Chain functions. This role is responsible for translating complex business requirements into scalable analytics, predictive, and conversational analytics solutions by leveraging deep domain expertise and modern data technologies.

The Associate Director will oversee solution architecture, data quality, advanced analytics development, and cross-functional collaboration to ensure high-impact, trusted, and transparent insights for the business.

• Technical Leadership and Strategy:
  Provide technical leadership in the development and implementation of Supply Chain, Finance and corporate function analytics solutions, aligning with business objectives and industry best practices.
• Execute Madrigal’s established enterprise data strategy, ensuring alignment with corporate, supply chain, and finance priorities and accelerating analytics delivery.
• Champion data governance, trust, and transparency by leveraging Alation for data cataloging, lineage, metadata management, and access control.
• Analytics Solution Architecture & Design:
  Architect scalable data pipelines and analytics platforms using Azure and Microsoft Fabric, enabling rapid insights and efficient data processing.
• Design and maintain semantic data models and dbt transformations to create well-governed, reusable, and trusted analytics layers.
• Build advanced Power BI dashboards, semantic models, dataflows, and Fabric‑based analytics workflows to support enterprise and self‑service reporting.
• Integrate Workday, Coupa, Net Suite, and other enterprise systems into unified, high-quality data models supporting corporate, finance, and supply chain analytics needs.
• Advanced Analytics, Predictive & Conversational Solutions:
  Lead the development of predictive models, optimization analytics workflows to support forecasting, financial planning, and supply chain optimization.
• Apply statistical modeling and advanced analytics to extract strategic insights from complex datasets.
• Deliver conversational analytics solutions to support self‑service and intuitive data access.
• Data Quality, Automation, Privacy & Trust:
  Develop and automate data quality rules, profiling, and anomaly detection to ensure accuracy, completeness, and consistency of analytics outputs.
• Implement data privacy and policy enforcement workflows using Immuta, ensuring secure, compliant, and governed access to sensitive datasets in partner with data owners/stewards.
• Drive enterprise-wide trust by establishing transparent data quality metrics, automated validation layers, and auditable pipelines inside Fabric, dbt, and Azure.
• Cross‑Functional Collaboration & Delivery Execution:
  Collaborate with business stakeholders, data engineers, data scientists, and system…