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[SD]- Engagement Lead- Analytics

procdna

About procdna

  • ProcDNA ProcDNA is a global rocket ship in life sciences consulting.
  • We fuse design thinking with cutting-edge tech to create game-changing Commercial Analytics and Technology solutions for our clients.
  • We're a passionate team of 450+ across 9 offices, all growing and learning together since our launch during the pandemic.
  • Here, you won't be stuck in a cubicle - you'll be out in the open water, shaping the future with brilliant minds.

Ready to join our epic growth journey?

What we are looking for We are seeking an Engagement Lead-Analytics to join our team—someone with a strong understanding of the pharmaceutical industry and detailed knowledge of datasets such as LAAD, DDD, and XPO.

You thrive on working with complex data sets to solve real-world problems and can translate insights into actionable business strategies.

In this role, you will be responsible for driving business performance, identifying and navigating risks, and developing pragmatic, data-driven strategies that deliver tangible impact.

Responsibilities

  • What you will do Lead forecasting engagements for pharma clients, driving business performance through robust, data-driven insights.
  • Develop and manage forecasting models for in-line and pipeline assets across multiple therapy areas.
  • Translate complex datasets and analytical findings into actionable business strategies and recommendations.
  • Collaborate with cross-functional client and internal teams to align on assumptions, scenarios, and methodologies.
  • Identify potential risks and opportunities impacting forecasts and deliver solutions to support decision-making.

Requirements

  • Contribute to building internal assets and forecasting accelerators Must Have 5–7 years of hands-on experience in pharmaceutical forecasting (inline and pipeline assets).
  • Strong understanding of key pharma datasets such as LAAD and other secondary data sources.
  • Proficiency in building and managing Excel-based forecasting models; exposure to advanced forecasting tools is a plus.
  • Excellent problem-solving skills with the ability to synthesize insights from complex data sets.
  • Strong communication and client management skills, with experience presenting insights to senior stakeholders.