Senior Director R&D Portfolio Data Strategy & Insights
Sanofi
2 days ago
Remote friendly (Morristown, NJ)
United States
Operations
Role / Responsibilities:
- Provide strategic leadership for Data, AI, GenAI, and Agentic AI tied to R&D Project and Portfolio Management business objectives.
- Lead delivery of a portfolio of new and mature AI data products.
- Build and improve foundational data assets and related governance for adoption across R&D project and portfolio management applications.
- Define and execute the FAIR data foundation (Findable, Accessible, Interoperable, Reusable) that enables portfolio analytics, reporting, and strategic decision-making.
- Transform data and AI strategy into execution at speed and at scale with R&D Operations and R&D Digital teams.
- Support the build and evolution of R&D portfolio and project management data foundations and enable data democratization.
- Drive operational innovation using advanced analytics, machine learning, computer vision, GenAI, and Agentic AI to optimize project and portfolio decision-making.
- Establish and maintain partnerships with internal stakeholders (e.g., Project Management, R&D Finance, Reporting, Portfolio Analytics, R&D Data Office, R&D Digital, GTMC).
- Prioritize and plan roadmaps for AI transformation initiatives across project and portfolio management.
- Develop and execute an enterprise data strategy; define data vision, roadmap, and strategic priorities.
- Lead digital transformation initiatives leveraging data as a strategic asset; drive organizational change management to foster a data-driven culture.
- Ensure data quality (accuracy, completeness) for portfolio and project domains; serve as subject matter expert.
- Take/identify data ownership; communicate data owner expectations for accountability of portfolio-critical data.
- Partner with Digital R&D to develop a GenAI-ready semantic layer for conversational self-service reporting and data exploration.
- Design and implement data governance frameworks; standardize and streamline data definitions across R&D systems.
- Partner with Master Data Management, Ontology, and Controlled Vocabulary initiatives to ensure interoperability and harmonization.
Qualifications / Required:
- Advanced degree (Ph.D., MBA, or equivalent) in life sciences, pharmaceutical sciences, Data Science, or related field.
- Minimum 10 years’ experience in portfolio data strategy, portfolio management, and analytics (or related) in pharmaceutical or biotechnology.
- Excellent leadership and communication skills; ability to influence stakeholders at all levels.
- Expert knowledge of data governance frameworks/methodologies.
- Strong track record in metadata management and data cataloging.
- Strong understanding of AI and machine learning principles, including data requirements; able to get hands-on as needed.
- Results-driven track record building and deploying data/AI systems into production and enabling end-user adoption.
- Knowledge of industry-standard data governance tools and platforms.
- Fluent English (written and verbal).
Preferred:
- Natural curiosity about AI trends; strategic problem-solving mindset; ability to operate in a matrix environment.
Benefits (explicitly mentioned):
- Wide range of health and wellbeing benefits, including high-quality healthcare, prevention and wellness programs, and at least 14 weeks’ gender-neutral parental leave.
Application instructions:
- None provided in the job description.
- Provide strategic leadership for Data, AI, GenAI, and Agentic AI tied to R&D Project and Portfolio Management business objectives.
- Lead delivery of a portfolio of new and mature AI data products.
- Build and improve foundational data assets and related governance for adoption across R&D project and portfolio management applications.
- Define and execute the FAIR data foundation (Findable, Accessible, Interoperable, Reusable) that enables portfolio analytics, reporting, and strategic decision-making.
- Transform data and AI strategy into execution at speed and at scale with R&D Operations and R&D Digital teams.
- Support the build and evolution of R&D portfolio and project management data foundations and enable data democratization.
- Drive operational innovation using advanced analytics, machine learning, computer vision, GenAI, and Agentic AI to optimize project and portfolio decision-making.
- Establish and maintain partnerships with internal stakeholders (e.g., Project Management, R&D Finance, Reporting, Portfolio Analytics, R&D Data Office, R&D Digital, GTMC).
- Prioritize and plan roadmaps for AI transformation initiatives across project and portfolio management.
- Develop and execute an enterprise data strategy; define data vision, roadmap, and strategic priorities.
- Lead digital transformation initiatives leveraging data as a strategic asset; drive organizational change management to foster a data-driven culture.
- Ensure data quality (accuracy, completeness) for portfolio and project domains; serve as subject matter expert.
- Take/identify data ownership; communicate data owner expectations for accountability of portfolio-critical data.
- Partner with Digital R&D to develop a GenAI-ready semantic layer for conversational self-service reporting and data exploration.
- Design and implement data governance frameworks; standardize and streamline data definitions across R&D systems.
- Partner with Master Data Management, Ontology, and Controlled Vocabulary initiatives to ensure interoperability and harmonization.
Qualifications / Required:
- Advanced degree (Ph.D., MBA, or equivalent) in life sciences, pharmaceutical sciences, Data Science, or related field.
- Minimum 10 years’ experience in portfolio data strategy, portfolio management, and analytics (or related) in pharmaceutical or biotechnology.
- Excellent leadership and communication skills; ability to influence stakeholders at all levels.
- Expert knowledge of data governance frameworks/methodologies.
- Strong track record in metadata management and data cataloging.
- Strong understanding of AI and machine learning principles, including data requirements; able to get hands-on as needed.
- Results-driven track record building and deploying data/AI systems into production and enabling end-user adoption.
- Knowledge of industry-standard data governance tools and platforms.
- Fluent English (written and verbal).
Preferred:
- Natural curiosity about AI trends; strategic problem-solving mindset; ability to operate in a matrix environment.
Benefits (explicitly mentioned):
- Wide range of health and wellbeing benefits, including high-quality healthcare, prevention and wellness programs, and at least 14 weeks’ gender-neutral parental leave.
Application instructions:
- None provided in the job description.