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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # enterprise IT AI - **Company:** Madrigal Pharmaceuticals - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $257,000.0 - $314,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Database, Python (Programming Language), Machine Learning, SQL Databases, Data Strategy, Information Technology, Machine Learning Operations, Veeva, Databricks - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/senior-director-advanced-analytics-products-madrigal-8839587 ## About the Role Typical Degree & Years of Experience * Bachelor's degree in a quantitative field such as statistics, data science, computer science, or engineering; advanced degree (MS or PhD) preferred. * 15+ years in pharmaceutical or biotech commercial advanced analytics, with demonstrated value generation across Sales, Patient Services, Market Access, and Marketing (e.g., omni-channel, attrition modeling, shareshift) * Fluency with core commercial data assets - specialty pharmacy / hub, claims (e.g., IQVIA, Symphony), CRM / Veeva, call and activity, and consent data - and the governed semantic layer built on them. * Experience partnering with technical teams to bring machine learning and AI-driven tools into production commercial workflows, with working knowledge of MLOps and model lifecycle management. * Demonstrated experience building, leading, and developing analytics or data science teams. * Hands-on proficiency in Python and SQL, and experience with cloud data and machine learning platforms (e.g., Databricks, Fabric, Azure/AWS ML tooling). Preferred * Experience applying evaluation and phased-rollout approaches (e.g., shadow-mode) for AI tools deployed on an enterprise platform. * Experience supporting specialty or rare disease brands. * Proven success in deploying AI workflow enhancements with focus on RoI Skills & Competencies * Deep fluency in the commercial operating model (field and home-office orchestration, market access, brand performance, patient services workflow optimization), paired with strong technical grounding and the judgment to prioritize high-ROI use cases. * Ability to build trust and evaluation rigor around new AI capabilities with non-technical stakeholders. * Effective cross-functional partnership across Commercial, Medical, IT, and the enterprise AI team, including translating business needs into technical requirements. * Proven people leadership and team development. ## Description The Senior Director, Commercial Advanced Analytics is the senior commercial-domain expert for advanced analytics and AI, translating deep knowledge of the Commercial business into high-value use cases and the requirements behind them. Reporting to the Executive Director of Data Strategy & Analytics, this leader works directly with Commercial leadership and functions to identify and prioritize high-value use cases, define the business requirements and success measures, and partner with the enterprise AI team - which builds, deploys, and governs the underlying models and AI capabilities - to embed them in commercial workflows and drive adoption. This role is focused on identifying, prioritizing, and being the "business owner" of Commercial advanced analytics / AI initiatives and products with a focus on enabling accelerated insights, optimizing workflows, and driving the ideation and adoption of critical capabilities. The enterprise IT AI team will be responsible for the hands-on build of these capabilities and deployment. Together, this partnership will deliver on accelerating Madrigal's Commercial success. Role & Responsibilities * Serve as Commercial PoC in defining and prioritizing the roadmap of commercial advanced analytics and AI use cases, in partnership with Commercial leadership and the enterprise AI team, which builds and deploys them on the enterprise platform * Own the advanced analytics roadmap and business integration of our next-best-action / omni-channel strategy with a focus on improving our customer engagement model through field and home office orchestration * Prioritize and manage the Commercial advanced-analytics and AI use-case pipeline, aligned to the enterprise intake, prioritization, and governance process * Define the business, data, and success requirements for Commercial models and AI tools, and partner with enterprise AI and IT in deployment and optimization of these tools * Provide commercial validation and business acceptance during enterprise-run testing and phased roll-outs, applying the enterprise evaluation framework and feeding Commercial requirements back to the enterprise AI * Own the day-to-day advanced analytics operations by serving as intake for Commercial leadership requests, structuring problem statements, working with our Enterprise AI team's dedicated Commercial Analytics AI resources to build appropriate solutions, and synthesizing these results into business-facing insights * Develop requirements to our Commercial Data Products team for enhancements to our semantic layer that enables trusted self-service, democratization of model outputs, and forward-looking natural-language querying * Serve as the Commercial-domain expert who translates business needs into advanced analytics and AI solutions, and represent Commercial requirements in the enterprise AI tool vendor evaluations ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [AI in High-Stakes Industries: Lessons Learned](https://www.wearedevelopers.com/videos/100253-ai-in-high-stakes-industries-lessons-learned) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)