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Global brand and metro location raise competition, but senior specialized forecasting reduces candidate pool.
Medium because core ML skills transfer, but healthcare/forecasting domain expertise is preferred.
High due to explicit 8+ years requirement and specialized Bayesian, probabilistic, and ML forecasting skills.
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Develop advanced statistical, Bayesian, and machine learning forecasting models for near-, medium-, and long-term demand planning.
Work end-to-end on modeling lifecycle including prototyping, data analysis, model development, deployment, and monitoring to support business decision-making.
Collaborate cross-functionally with Commercial, Operation, Finance, and Technology teams to integrate forecasts into critical business workflows and build simulation/scenario analysis capabilities.
8+ years of data science experience in enterprise environments with proven business impact.
Expertise in time-series forecasting, probabilistic programming, Bayesian and predictive modeling.
Proficient in Python, SQL, and data science libraries such as scikit-learn, PyMC, Pytorch, Tensorflow.
Strong analytical skills with experience in latent variable modeling, high dimensional clustering, causal inference, and quasi-experimental methods.
Experienced in deploying forecasting models particularly within biotech/pharma or healthcare commercial contexts involving payer/provider dynamics.
Skilled in handling large, complex datasets and applying state-of-the-art forecasting and machine learning techniques.
Able to translate complex technical concepts into clear insights for non-technical stakeholders and work effectively across departments.