Director, Advanced Analytics, Field Force Strategy & Effectiveness

Legend Biotech USBridgewater, NJ
$193,629 - $254,137Hybrid

About The Position

Legend Biotech is seeking a Director, Advanced Analytics, Field Force Strategy & Effectiveness as part of the Insights and Analytics team based in Bridgewater, NJ. This is a senior leadership role responsible for shaping and driving the enterprise Sales Force Effectiveness (SFE) strategy through advanced analytics, predictive modeling, and decision science. This role serves as the analytic and strategic authority for SFE—owning complex, high-impact initiatives such as territory alignment, customer targeting, incentive compensation design, and field deployment strategy that directly influence commercial performance and investment decisions. Operating at the intersection of analytics, commercial strategy, Sales Operations, and HR, the Director is expected to lead end-to-end initiatives, influence senior stakeholders, and translate complex analytics into clear, actionable recommendations that shape how the field force is deployed and managed across the organization.

Requirements

  • Master’s degree preferred; bachelor’s degree required in Statistics, Data Science, Mathematics, Econometrics, Computer Science, Public Health (quantitative focus), or a related field.
  • 10+ years of progressive experience in advanced analytics, data science, or commercial insights within the pharmaceutical or life sciences industry.
  • Demonstrated leadership of complex Sales Force Effectiveness initiatives, including territory alignment, customer targeting, incentive compensation design, and field deployment strategy.
  • Proven ability to lead initiatives independently, influence cross-functional stakeholders, and operate at the senior-leadership interface.
  • Deep hands-on experience with pharma secondary data (e.g., IQVIA, Symphony, DRG), CRM data, and commercial data ecosystems.
  • Advanced expertise in statistical modeling and analytics (e.g., regression, classification, clustering, forecasting).
  • Strong commercial acumen with a clear understanding of field execution, incentives, and sales strategy.
  • Exceptional communication skills with a demonstrated ability to translate complex analytics into actionable insights for executive and non-technical audiences.

Responsibilities

  • Own the analytical design and governance of territory alignment, field sizing, and resource deployment strategies to optimize coverage, productivity, and return on investment.
  • Lead customer targeting, segmentation, and prioritization analytics, translating sophisticated models into field-ready strategies (e.g., segment definitions, reach and frequency guidance) that can be operationalized by Sales Operations and adopted by the field.
  • Design, evaluate, and evolve incentive compensation models, including quota methodologies, payout structures, and performance scenarios.
  • Assess incentive plan effectiveness through post-cycle analytics, identifying behavioral responses, unintended consequences, and optimization opportunities.
  • Partner closely with Sales Operations and HR on incentive governance while maintaining analytical rigor and independence.
  • Lead and own enterprise-level advanced analytics initiatives supporting field force strategy, acting as the primary advisor to Sales Leadership, Sales Operations, and Insights & Analytics leadership on all SFE-related decisions.
  • Set the analytical vision and roadmap for SFE, ensuring alignment with broader commercial strategy and long-term capability development.
  • Serve as the escalation point and decision authority for complex SFE tradeoffs, methodology choices, and investment decisions.
  • Function as a trusted analytics partner to senior stakeholders across Commercial, Sales Operations, HR, and Finance.
  • Lead cross-functional working teams to drive SFE initiatives from concept through implementation.
  • Influence senior leaders through clear storytelling, structured recommendations, and data-driven foresight.
  • Apply advanced predictive modeling and machine learning techniques to forecast field performance, identify key growth drivers, and diagnose drivers of under- and over-performance.
  • Deliver prescriptive recommendations that improve field execution, productivity, and commercial outcomes.
  • Ensure analytical outputs are decision-oriented and directly inform leadership actions.

Benefits

  • Medical, dental, and vision insurance
  • 401(k) retirement plan with a company match that vests fully on day one
  • Eight (8) weeks of paid parental leave after just three (3) months of employment
  • Paid time off policy that includes vacation time, personal time, sick time, floating holidays, and eleven (11) company holidays
  • Flexible spending and health savings accounts
  • Life and AD&D insurance
  • Short- and long-term disability coverage
  • Legal assistance
  • Supplemental plans such as pet, critical illness, accident, and hospital indemnity insurance
  • Voluntary commuter benefits
  • Family planning and care resources
  • Well-being initiatives
  • Peer-to-peer recognition programs
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