Senior Director R&D Portfolio Data Strategy & Insights
Sanofi
9 hours ago
Remote friendly (Cambridge, MA)
United States
IT
Role / Responsibilities:
- Provide strategic leadership for Data, AI, GenAI, and Agentic AI tied to R&D Project and Portfolio Management objectives.
- Lead delivery of new and mature AI data products to generate transformational impact.
- Build and improve foundational data assets and related governance for adoption across R&D project and Portfolio Management applications.
- Align digital transformation roadmaps with business objectives and operational excellence goals.
- Transform Data/AI strategy into execution at speed and at scale with R&D Operations and R&D Digital.
- Support the build/evolution of R&D Portfolio and Project Management data foundations and data democratization.
- Drive operational innovation using advanced analytics, machine learning, computer vision, GenAI, and Agentic AI to optimize project/portfolio decision-making.
- Establish and maintain strategic partnerships with internal stakeholders (Project Management, Project Resource Management, R&D Finance, Reporting, Portfolio Analytics, R&D Data Office, R&D Digital, GTMC).
- Lead prioritization and roadmap planning for AI transformation across Project and Portfolio Management.
- Develop and execute an enterprise data strategy aligned to business objectives and scientific mission; define data vision, roadmap, and priorities.
- Lead digital transformation leveraging data as a strategic asset and drive organizational change for a data-driven culture.
- Ensure data quality (quality, accuracy, completeness) for operational efficiency and portfolio analytics.
- Take data ownership/identify data owners; set expectations for portfolio-critical data accountability.
- Support development of a GenAI-ready semantic layer for conversational self-service reporting and data exploration.
- Design and implement comprehensive data governance frameworks; standardize/streamline data definitions.
- Partner with Master Data Management, Ontology, and Controlled Vocabulary initiatives to enable interoperability and harmonization.
Qualifications / Skills:
- Required: Advanced degree (Ph.D., MBA, or equivalent) in life sciences, pharmaceutical sciences, Data Science, or related field.
- Required: 10+ years’ experience in portfolio data strategy, portfolio management, and analytics (pharma/biotech).
- 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.
- Proven ability to lead/develop capabilities and collaborate cross-functionally.
- Mature leadership skills for senior-level influence in a matrix environment.
- Strong understanding of AI and machine learning principles, including data requirements; able to be hands-on and pressure test.
- Strategic problem-solving mindset; ability to arbitrate in business context and drive outcomes.
- Results-driven track record building/deploying data and AI systems into production and enabling adoption.
- Knowledge of industry-standard data governance tools and platforms.
- Fluent English (written and verbal).
Benefits:
- Health and wellbeing benefits, including high-quality healthcare and prevention/wellness programs.
- At least 14 weeks’ gender-neutral parental leave.
Application Instructions:
- Not specified in the provided text.
- Provide strategic leadership for Data, AI, GenAI, and Agentic AI tied to R&D Project and Portfolio Management objectives.
- Lead delivery of new and mature AI data products to generate transformational impact.
- Build and improve foundational data assets and related governance for adoption across R&D project and Portfolio Management applications.
- Align digital transformation roadmaps with business objectives and operational excellence goals.
- Transform Data/AI strategy into execution at speed and at scale with R&D Operations and R&D Digital.
- Support the build/evolution of R&D Portfolio and Project Management data foundations and data democratization.
- Drive operational innovation using advanced analytics, machine learning, computer vision, GenAI, and Agentic AI to optimize project/portfolio decision-making.
- Establish and maintain strategic partnerships with internal stakeholders (Project Management, Project Resource Management, R&D Finance, Reporting, Portfolio Analytics, R&D Data Office, R&D Digital, GTMC).
- Lead prioritization and roadmap planning for AI transformation across Project and Portfolio Management.
- Develop and execute an enterprise data strategy aligned to business objectives and scientific mission; define data vision, roadmap, and priorities.
- Lead digital transformation leveraging data as a strategic asset and drive organizational change for a data-driven culture.
- Ensure data quality (quality, accuracy, completeness) for operational efficiency and portfolio analytics.
- Take data ownership/identify data owners; set expectations for portfolio-critical data accountability.
- Support development of a GenAI-ready semantic layer for conversational self-service reporting and data exploration.
- Design and implement comprehensive data governance frameworks; standardize/streamline data definitions.
- Partner with Master Data Management, Ontology, and Controlled Vocabulary initiatives to enable interoperability and harmonization.
Qualifications / Skills:
- Required: Advanced degree (Ph.D., MBA, or equivalent) in life sciences, pharmaceutical sciences, Data Science, or related field.
- Required: 10+ years’ experience in portfolio data strategy, portfolio management, and analytics (pharma/biotech).
- 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.
- Proven ability to lead/develop capabilities and collaborate cross-functionally.
- Mature leadership skills for senior-level influence in a matrix environment.
- Strong understanding of AI and machine learning principles, including data requirements; able to be hands-on and pressure test.
- Strategic problem-solving mindset; ability to arbitrate in business context and drive outcomes.
- Results-driven track record building/deploying data and AI systems into production and enabling adoption.
- Knowledge of industry-standard data governance tools and platforms.
- Fluent English (written and verbal).
Benefits:
- Health and wellbeing benefits, including high-quality healthcare and prevention/wellness programs.
- At least 14 weeks’ gender-neutral parental leave.
Application Instructions:
- Not specified in the provided text.