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Tier-1 employer and metro location raise competition, though seniority and niche forecasting skills moderate applicant density.
Strong ML forecasting skills are transferable, but biotech/pharma domain knowledge preferred increases industry specificity.
Explicit 8+ years requirement plus deep ML, Bayesian, and production deployment skills make filters strict.
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Develop advanced statistical, Bayesian, and machine learning models to forecast demand across multiple planning horizons (near-, medium-, long-term).
Work with large, complex datasets to generate strategic insights using forecasting, causal inference, and analytics techniques.
Collaborate cross-functionally to integrate forecasting solutions into critical business workflows, supporting multi-horizon planning and decision-making.
8+ years of data science experience in enterprise environments with a proven track record of delivering business value.
Expertise in time-series forecasting, probabilistic programming, Bayesian and predictive modeling.
Proficiency in Python, SQL, and libraries such as scikit-learn, PyMC, Pytorch, Tensorflow.
Work Location: On site in Hyderabad, India.
Experienced in applying statistical and machine learning forecasting methods to complex, high-dimensional data in enterprise settings.
Able to communicate technical concepts effectively to non-technical stakeholders and influence cross-functional teams.
Has domain knowledge in biotech/pharma forecasting or related applications in retail, consumer goods, supply chain, or manufacturing.