Pharma Analytics & Forecasting Lead

ProcDNA; San Francisco (CA); On-site; USD 180,000 - 250,000; Full time

Job summary

ProcDNA in San Francisco seeks a Senior Engagement Lead - Analytics to steer pharma forecasting engagements, translating complex data into strategic business actions. You will build and manage Excel-based models for inline and pipeline assets and work with LAAD datasets and related sources.

You'll collaborate with cross-functional teams and senior stakeholders to align assumptions, assess risks, and deliver data-driven recommendations that improve forecast accuracy and business performance.

Qualifications

• 8–10 years of hands-on experience in pharmaceutical forecasting (inline and pipeline assets).
• Strong understanding of LAAD datasets and other secondary data sources.
• Proficiency in building Excel-based forecasting models; exposure to forecasting tools is a plus.
• Excellent problem-solving and senior stakeholder communication skills.

Responsibilities

• Lead forecasting engagements for pharma clients and drive business performance.
• Develop and manage forecasting models for inline and pipeline assets across therapy areas.
• Translate analyses into actionable business strategies and recommendations.
• Collaborate with cross-functional teams to align assumptions and methodologies.
• Identify risks and opportunities affecting forecasts and propose solutions.
• Contribute to building internal assets and forecasting accelerators.

Skills

Pharma forecasting

Excel forecasting models

Data analysis

Stakeholder communication

Forecasting tools

Tools

Excel

Forecasting software

Job description

ProcDNA in San Francisco seeks a Senior Engagement Lead - Analytics to steer pharma forecasting engagements, translating complex data into strategic business actions. You will build and manage Excel-based models for inline and pipeline assets and work with LAAD datasets and related sources.

You'll collaborate with cross-functional teams and senior stakeholders to align assumptions, assess risks, and deliver data-driven recommendations that improve forecast accuracy and business performance.