Lead, Decision Data & Intelligence Enablement
Novartis
June 25, 2026
Remote friendly (Cambridge, MA)
United States
IT
Job responsibilities:
- Own and define a portfolio of decision-grade data products for enterprise portfolio decision making, including standards, stewardship, and accountability models across systems and partners.
- Establish and maintain data quality standards and trust indicators; make data fitness for decision use visible, measurable, and transparent at leadership level.
- Drive enterprise trust reporting; proactively identify recurring trust issues and prioritize systemic prevention over repeated remediation.
- Identify, prioritize, and lead high-impact AI, automation, and advanced analytics use cases, grounded in trusted data and scaled with clear business impact.
- Act as a key driver of the AI & automation agenda, translating opportunities into scalable, enterprise-grade capabilities.
- Be the primary accountability point for decision trust issues, communicating risks, confidence levels, and systemic resolution.
Key Performance Indicators:
- Adoption of a clearly defined portfolio of decision-grade data products and standards.
- Measurable improvement in data trust indicators over time.
- Reduction in recurrence of data trust issues via proactive monitoring and design-time prevention.
- Delivery and scaled adoption of high-impact AI/automation (incl. agent-based capabilities) enabling trusted, self-service decision data access.
- Measurable improvement in decision-making efficiency and speed (e.g., reduced manual effort, faster insight access).
Essential requirements:
- 7+ years of relevant pharmaceutical/AI/consultant experience.
- Bachelor’s degree required; advanced degree preferred.
- Experience defining/managing enterprise data products, data quality standards, trust indicators, and governance models.
- Ability to establish data stewardship and accountability across complex, multi-system environments.
- Proven track record owning AI/automation/advanced analytics initiatives through scalable adoption.
- Ability to translate AI/analytics into enterprise decision impact, including confidence signals, usage guidance, and guardrails.
- Influence without authority; align stakeholders across business, digital, architecture, and delivery teams.
- Negotiation skills managing trade-offs (speed vs quality; local vs enterprise).
- Proactive problem-solving; anticipate risks/roadblocks and drive mitigation.
- Executive communication of data trust, risks, confidence, and decision implications.
Desirable requirements:
- Strong data/analytical literacy (e.g., SQL, Python, BI tools) and enterprise data architecture knowledge.
- Experience in enterprise portfolio/R&D/pharma decision-making environments.
- Experience working with global teams and scaling solutions.
- Experience embedding data quality, trust, and AI readiness into system design with architecture teams.
Benefits & rewards:
- Salary expected range: $145,600–$270,400/year; performance-based cash incentive; eligibility for annual equity awards (depending on level). US-based eligible employees receive comprehensive benefits and time off.
- Own and define a portfolio of decision-grade data products for enterprise portfolio decision making, including standards, stewardship, and accountability models across systems and partners.
- Establish and maintain data quality standards and trust indicators; make data fitness for decision use visible, measurable, and transparent at leadership level.
- Drive enterprise trust reporting; proactively identify recurring trust issues and prioritize systemic prevention over repeated remediation.
- Identify, prioritize, and lead high-impact AI, automation, and advanced analytics use cases, grounded in trusted data and scaled with clear business impact.
- Act as a key driver of the AI & automation agenda, translating opportunities into scalable, enterprise-grade capabilities.
- Be the primary accountability point for decision trust issues, communicating risks, confidence levels, and systemic resolution.
Key Performance Indicators:
- Adoption of a clearly defined portfolio of decision-grade data products and standards.
- Measurable improvement in data trust indicators over time.
- Reduction in recurrence of data trust issues via proactive monitoring and design-time prevention.
- Delivery and scaled adoption of high-impact AI/automation (incl. agent-based capabilities) enabling trusted, self-service decision data access.
- Measurable improvement in decision-making efficiency and speed (e.g., reduced manual effort, faster insight access).
Essential requirements:
- 7+ years of relevant pharmaceutical/AI/consultant experience.
- Bachelor’s degree required; advanced degree preferred.
- Experience defining/managing enterprise data products, data quality standards, trust indicators, and governance models.
- Ability to establish data stewardship and accountability across complex, multi-system environments.
- Proven track record owning AI/automation/advanced analytics initiatives through scalable adoption.
- Ability to translate AI/analytics into enterprise decision impact, including confidence signals, usage guidance, and guardrails.
- Influence without authority; align stakeholders across business, digital, architecture, and delivery teams.
- Negotiation skills managing trade-offs (speed vs quality; local vs enterprise).
- Proactive problem-solving; anticipate risks/roadblocks and drive mitigation.
- Executive communication of data trust, risks, confidence, and decision implications.
Desirable requirements:
- Strong data/analytical literacy (e.g., SQL, Python, BI tools) and enterprise data architecture knowledge.
- Experience in enterprise portfolio/R&D/pharma decision-making environments.
- Experience working with global teams and scaling solutions.
- Experience embedding data quality, trust, and AI readiness into system design with architecture teams.
Benefits & rewards:
- Salary expected range: $145,600–$270,400/year; performance-based cash incentive; eligibility for annual equity awards (depending on level). US-based eligible employees receive comprehensive benefits and time off.