Director, AI Analytics and Reporting Enablement
Scorpion Therapeutics, New Philadelphia, PA, United States
Role Summary
Location: Philadelphia, PA, USA. The Director, AI Analytics & Reporting Enablement provides strategic leadership for enterprise analytics transformation within U.S. Commercial, owning the vision, strategy, and execution for scalable BI, GenAI, and advanced analytics capabilities. They enable data-driven decision-making across marketing, sales, market access, patient services, and enterprise teams, and set the long-term analytics enablement roadmap while ensuring governed, compliant data usage. The role combines hands‑on BI/AI work with strategic leadership, mentoring a cross‑functional team to drive innovation, operational excellence, and measurable business impact. Responsibilities
Strategy & Roadmap - Define and execute the multi-year strategy for enterprise BI, AI, and analytics enablement to maximize commercial impact. Commercial Use Case Prioritization - Identify, evaluate, and prioritize high-value analytics and AI use cases that advance brand, access, field, and omnichannel objectives. Platform Ownership - Serve as product owner for the AI enterprise analytics ecosystem, ensuring solutions are scalable, integrated, and user‑centric. Governance & Compliance - Establish and maintain governance standards for data quality, semantic modeling, AI/ML lifecycle, and compliant analytics practices. Player‑Coach Leadership - Lead, mentor, and develop the AI analytics enablement team while personally contributing hands‑on to BI development and problem‑solving. Stakeholder Partnership - Act as a strategic advisor to senior commercial leaders by translating analytics capabilities into clear business decisions and outcomes. AI/ML & GenAI Innovation - Drive evaluation, piloting, and scaling of advanced analytics, AI/ML, and GenAI solutions that enhance commercial performance. Operational Excellence - Oversee delivery of high‑quality dashboards, reporting tools, and insight workflows that improve speed‑to‑decision and data reliability. Adoption & Change Management - Lead adoption efforts through training, storytelling, and change leadership to embed AI‑first, data‑driven ways of working. Vendor & Budget Oversight - Manage vendors, contracts, and analytics investments to ensure cost‑efficient delivery of high‑value capabilities. Qualifications
Required: Bachelor’s degree in quantitative or business discipline Required: At least 10 years of experience in analytics, data science, or business intelligence Required: At least 5 years of experience leading functional or cross‑functional teams and driving cross‑functional analytics initiatives Required: Experience scaling analytics platforms and driving broad enterprise adoption Required: Hands‑on experience with ThoughtSpot and Liveboards Required: Fluent in SQL, semantic modeling concepts, cloud data environments, and key commercial data sources (such as patient‑level claims) Required: Proven track record of translating analytics into clear business impact as well as influencing senior stakeholders Required: Experience in balancing strategic leadership with hands‑on technical contribution Preferred: MBA or advanced degree in Data Science, Statistics, Computer Science, or related field Preferred: 15+ years of experience in analytics, data science, or business intelligence Preferred: 8+ years of experience leading functional or cross‑functional teams and driving analytics initiatives Preferred: Hands‑on experience with BI/analytics tools (ThoughtSpot, Tableau, Power BI) including semantic data modeling Preferred: Familiarity with cloud environments (AWS, Azure, GCP) and data technologies (Spark, Databricks) Preferred: Proven track record leading, building and scaling advanced analytics, AI/ML, and GenAI solutions Preferred: Ability to simplify complex analytics into compelling, actionable business narratives Preferred: Proven track record influencing VP‑level stakeholders and navigating complex cross‑functional environments Education
Bachelor’s degree in quantitative or business discipline MBA or advanced degree in Data Science, Statistics, Computer Science, or related field
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Location: Philadelphia, PA, USA. The Director, AI Analytics & Reporting Enablement provides strategic leadership for enterprise analytics transformation within U.S. Commercial, owning the vision, strategy, and execution for scalable BI, GenAI, and advanced analytics capabilities. They enable data-driven decision-making across marketing, sales, market access, patient services, and enterprise teams, and set the long-term analytics enablement roadmap while ensuring governed, compliant data usage. The role combines hands‑on BI/AI work with strategic leadership, mentoring a cross‑functional team to drive innovation, operational excellence, and measurable business impact. Responsibilities
Strategy & Roadmap - Define and execute the multi-year strategy for enterprise BI, AI, and analytics enablement to maximize commercial impact. Commercial Use Case Prioritization - Identify, evaluate, and prioritize high-value analytics and AI use cases that advance brand, access, field, and omnichannel objectives. Platform Ownership - Serve as product owner for the AI enterprise analytics ecosystem, ensuring solutions are scalable, integrated, and user‑centric. Governance & Compliance - Establish and maintain governance standards for data quality, semantic modeling, AI/ML lifecycle, and compliant analytics practices. Player‑Coach Leadership - Lead, mentor, and develop the AI analytics enablement team while personally contributing hands‑on to BI development and problem‑solving. Stakeholder Partnership - Act as a strategic advisor to senior commercial leaders by translating analytics capabilities into clear business decisions and outcomes. AI/ML & GenAI Innovation - Drive evaluation, piloting, and scaling of advanced analytics, AI/ML, and GenAI solutions that enhance commercial performance. Operational Excellence - Oversee delivery of high‑quality dashboards, reporting tools, and insight workflows that improve speed‑to‑decision and data reliability. Adoption & Change Management - Lead adoption efforts through training, storytelling, and change leadership to embed AI‑first, data‑driven ways of working. Vendor & Budget Oversight - Manage vendors, contracts, and analytics investments to ensure cost‑efficient delivery of high‑value capabilities. Qualifications
Required: Bachelor’s degree in quantitative or business discipline Required: At least 10 years of experience in analytics, data science, or business intelligence Required: At least 5 years of experience leading functional or cross‑functional teams and driving cross‑functional analytics initiatives Required: Experience scaling analytics platforms and driving broad enterprise adoption Required: Hands‑on experience with ThoughtSpot and Liveboards Required: Fluent in SQL, semantic modeling concepts, cloud data environments, and key commercial data sources (such as patient‑level claims) Required: Proven track record of translating analytics into clear business impact as well as influencing senior stakeholders Required: Experience in balancing strategic leadership with hands‑on technical contribution Preferred: MBA or advanced degree in Data Science, Statistics, Computer Science, or related field Preferred: 15+ years of experience in analytics, data science, or business intelligence Preferred: 8+ years of experience leading functional or cross‑functional teams and driving analytics initiatives Preferred: Hands‑on experience with BI/analytics tools (ThoughtSpot, Tableau, Power BI) including semantic data modeling Preferred: Familiarity with cloud environments (AWS, Azure, GCP) and data technologies (Spark, Databricks) Preferred: Proven track record leading, building and scaling advanced analytics, AI/ML, and GenAI solutions Preferred: Ability to simplify complex analytics into compelling, actionable business narratives Preferred: Proven track record influencing VP‑level stakeholders and navigating complex cross‑functional environments Education
Bachelor’s degree in quantitative or business discipline MBA or advanced degree in Data Science, Statistics, Computer Science, or related field
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