The position also requires 6 years of experience in the following skills: Develop patient-based forecasting models, including dynamic patient flow modeling and cohort-based projections, to inform product strategy in the biopharmaceutical industry; Quantitative analysis techniques, including statistical trending, time series analysis, regression modeling, smoothing techniques, and Monte Carlo simulation; Utilize commercial pharmaceutical datasets, including IQVIA such as Xponent, Symphony Health, National Audit Rx, and longitudinal patient data such as LAAD (Longitudinal Access and Adjudicated Data) for forecast development and market insights; Experience with global epidemiology data for incidence, prevalence, treatment rates, and line-of-therapy progression to support forecast modeling and strategic planning; Knowledge of global market access and reimbursement frameworks, including the ability to incorporate payer landscape and policy scenarios into forecasting and business decision models; Excel functions and forecasting tools, including pivot tables, lookup formulas, scenario modeling, and probabilistic modeling using software such as Microsoft Excel and RISK or Crystal Ball; Experience in oncology therapeutic area, with working knowledge of immuno-oncology (I/O) treatment paradigms, novel emerging classes, competitive landscape, and clinical development trends; and. Develop an objective point of view of brand strategy by integrating insights across multiple functions and capability areas; Leverage communication and interpersonal skills to influence leadership on recommended course of action; Quantify uncertainty with scenario planning and advanced simulation models including Monte Carlo analysis and statistical trending; Utilize an in-depth understanding of diverse pharmaceutical data sources such as LAAD, National Audit Rx, Xponent, Epidemiology data sources and their nuances to develop and implement enhanced forecasting approaches and methodologies; Create and deliver effective presentations that are transparent and articulate all key variables in the forecast, ensuring clarity and comprehensive understanding for stakeholders involved in decision-making processes; Collaborate with the broader CD&A (Commercial Data & Analytics) organization to integrate comprehensive insights and analytics knowledge into the development and refinement of forecasts to enhance the depth and accuracy of forecasts by leveraging a broad spectrum of insights across the organization; and Drive productivity and efficiency, streamlining forecasting processes where possible, developing best practices and leading internal forecasting initiatives as appropriate.