Neuroscience Portfolio Insights Lead | Hybrid

AbbVie; South San Francisco (CA); Hybrid; USD 142,000 - 269,000; Full time

Job summary

AbbVie is seeking an Associate Director, Portfolio Insights – Neuroscience TA, to lead analytics and coordinate inputs across functions for portfolio decisions. You will present recommendations to TA leadership and mentor teams in valuation, scenario analysis, and decision support.

The role emphasizes cross-functional collaboration, enterprise thinking, and advancing analytics with modernized approaches, including AI/ML, to drive better drug development decisions.

Qualifications

• Bachelor's degree in scientific or business field required; MBA and PhD in scientific field preferred.
• Demonstrated analytical and problem-solving skills with attention to detail.
• Experience communicating complex analyses to diverse audiences.

Responsibilities

• Deliver high-impact recommendations on project value, trade-offs and scenarios to senior leadership.
• Identify opportunities where valuation and economic analysis improve asset strategy decisions.
• Build value metrics (e.g., raNPV, PI) and scenario analyses to guide drug development decisions.
• Coach team members on valuations and data-driven decision-making.
• Engage with stakeholders to drive linkages and stress-test inputs.
• Support Portfolio Insights processes including R&D planning, prioritization and productivity.

Skills

Analytical skills

Problem solving

Communication (oral & written)

Project management

Stakeholder management

Education

Bachelor's degree (scientific or business)

MBA

PhD

Job description

AbbVie is seeking an Associate Director, Portfolio Insights – Neuroscience TA, to lead analytics and coordinate inputs across functions for portfolio decisions. You will present recommendations to TA leadership and mentor teams in valuation, scenario analysis, and decision support.

The role emphasizes cross-functional collaboration, enterprise thinking, and advancing analytics with modernized approaches, including AI/ML, to drive better drug development decisions.