Director of Digital Product Management

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💎 Seniority level: Director, 4+ years

📍 Location: United States

💸 Salary: 194717.0 - 246921.0 USD per year

🔍 Industry: Biopharma

🏢 Company: careers

⏳ Experience: 4+ years

🪄 Skills: AWSLeadershipProject ManagementSQLAgileArtificial IntelligenceData AnalysisGCPMachine LearningPeople ManagementProduct ManagementCross-functional Team LeadershipData scienceRDBMSStakeholder managementStrategic thinkingData modeling

Requirements:

8+ years of product management experience, with at least 3 years leading Artificial Intelligence /Machine Learning driven products in biopharma or life sciences.
Deep understanding of clinical trial operations, regulatory pathways, and biopharma commercialization strategies. Demonstrable ability to define and meet KPIs with AI/ML driven capabilities.
Solid understanding of AI/ML technologies, including natural language processing, predictive analytics, and real-world data applications.
Proven experience managing cross-functional teams and influencing senior and end user partners.
Familiarity with global regulatory frameworks (e.g., FDA, EMA, ICH guidelines) as they relate to AI applications in biopharma.
Experience working with real-world evidence (RWE) and healthcare data sources.
Background in AI ethics and responsible AI principles in healthcare.
Track record of launching AI solutions in a highly regulated industry.

Responsibilities:

Define the vision, strategy, and roadmap for AI-powered products supporting clinical trials through commercialization in biopharma.
Collaborate with cross-functional teams, including data science, engineering, and data teams, to develop AI solutions that improve trial design, patient recruitment, and commercial decision-making.
Drive the end-to-end AI product lifecycle from ideation to go to market, ensuring alignment with business objectives and regulatory requirements.
Partner with biopharma clients, healthcare professionals, and regulatory agencies to understand needs and ensure AI solutions meet industry standards.
Stay ahead of advancements in AI, machine learning, and NLP applications within the biopharma industry, integrating standard processes into product development.
Ensure ethical AI principles and compliance with regulatory guidelines, including GxP, HIPAA, and FDA/EMA requirements.
Define and track key performance metrics for AI product effectiveness and adoption.

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