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Tier-1 brand, Hyderabad metro, and generalist analytics role increase applicant competition.
Pharma forecasting preference reduces transferability despite broadly transferable data science skills.
Explicit 1–3 years plus pharma forecasting and strong Python/scikit-learn requirements raise filter strictness.
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Develop, maintain, and automate end-to-end forecasting models with emphasis on Python implementations for patient-based, epidemiological, and scenario-driven forecasts.
Lead digitalization of forecasting processes, transitioning manual or spreadsheet models into automated, reproducible Python workflows.
Analyze complex datasets to generate actionable insights, collaborate with Commercial and Finance teams to optimize forecasting KPIs and business processes.
1-3 years experience in a business analyst role, preferably in biopharma or pharmaceutical industry.
Bachelor’s or master’s degree in pharmacy, technology, or engineering with strong analytical and quantitative skills.
Strong Python proficiency, including libraries such as pandas, NumPy, scikit-learn, and experience integrating Python with visualization/reporting tools (Tableau, Power BI).
Experience in short-term and strategic forecasting in pharma; advanced skills in MS Excel and PowerPoint, VBA and Macros preferred.
Experienced in forecasting models and analytics in complex pharma industry environments involving senior management engagement.
Comfortable with end-to-end automation and digital transformation of forecasting workflows using Python and data science tools.
Capable of partnering cross-functionally with Commercial and Finance teams, focusing on delivering KPI-driven insights and optimizing forecasting processes.