Forecasting

• Lead therapy-area-specific forecasting engagements, ensuring delivery of high-quality, well-documented, and strategically relevant models
• Design and develop custom forecast models using patient-based, analog-based, and market-based approaches depending on product lifecycle stage
• Apply deep understanding of disease epidemiology, treatment flow, claims data, and analogs to support robust assumptions
• Manage structured forecast processes – including assumption alignment, validation with stakeholders, and scenario modeling
• Lead discussions with clients on forecast inputs, model drivers, and commercial implications
• Collaborate with internal stakeholders including patient analytics, market research, and advanced analytics teams to enrich forecasts
• Drive innovation and consistency in forecasting methodology, template standardization, and reusable frameworks
• Support forecasting input into strategic deliverables including brand planning, launch readiness, market access strategy, and business case development
• Supervise and mentor a team of consultants/analysts on forecast building, QA, documentation, and client communication
• Support business development efforts through proposal development and forecast solutioning

You’ll need to have:

• 9+ years of experience in commercial pharma analytics, with a proven track record of delivering impactful solutions in the pharmaceutical and life sciences industry (Hands-on experience is preferred). Atleast 5 years of direct experience in pharmaceutical forecasting, preferably in a consulting environment (ZS, Axtria, IQVIA, or similar)
• Bachelor’s or Master’s degree in Life Sciences, Pharmacy, Economics, Engineering, or a quantitative field; MBA or MPH preferred
• Strong familiarity with forecasting approaches across early, pre-launch, launch, and in-market assets. Experience working across multiple therapeutic areas including specialty care, rare diseases, or oncology
• Advanced proficiency in statistical forecasting methods (time series analysis, regression modeling, predictive analytics) is a must. Experience with forecasting software and tools (SAS, R, Python, SPSS, or specialized platforms like Anaplan, Oracle EPM, SAP IBP) is good to have
• Knowledge of demand planning, sales forecasting, and financial modeling techniques is required. Understanding of seasonality, trend analysis, and scenario planning methodologies is a must.

• Advanced Excel modeling skills; ability to build, audit, and refine structured forecast models. Understanding of core statistical and analytical techniques used in forecasting (sensitivity analysis, back-casting, calibration)
• Strong Excel skills including advanced functions, pivot tables, and VBA/macros is required
• Experience in dashboarding tools (Power BI, Tableau) and scripting tools (R, Python) is a plus