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Tier-1 brand, popular Data Scientist title, and metro Hyderabad increase competition.
Advanced forecasting and pharma commercial knowledge preference creates moderate industry specificity but transferable modeling skills.
Explicit 8+ years, domain forecasting experience, and mandatory tech stack raise shortlisting strictness.
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Develop and implement advanced statistical, Bayesian, and machine learning models for multi-horizon demand forecasting to support strategic business decisions.
Manage the end-to-end modeling lifecycle including data analysis, feature engineering, deployment, and ongoing model monitoring with explainability.
Collaborate cross-functionally with Commercial, Operation, Finance, and Technology teams to integrate forecasts into critical business workflows and develop scenario-analysis capabilities.
8+ years of experience applying data science in enterprise environments with a proven track record of delivering business value.
Expertise in time-series forecasting, probabilistic programming, Bayesian and predictive modeling.
Strong proficiency in Python, SQL, and data science libraries such as scikit-learn, PyMC, Pytorch, and Tensorflow.
Work Experience Required: 8+ years in data science roles; Notice Period: Not explicitly mentioned in the JD.
Experienced in applying forecasting models within biotech/pharma or related domains with understanding of healthcare commercial concepts.
Capable of handling complex, high-dimensional datasets using advanced analytical methods like latent variable modeling and causal inference.
Demonstrates ability to translate technical forecasts into actionable insights for non-technical stakeholders and work effectively in cross-functional teams.