Senior Data Scientist

Overview

Senior Data Scientist (Forecasting) to build advanced statistical, Bayesian, causal, and machine learning models that improve demand forecasting and quantify uncertainty for strategic decisions.

What you'll do

• Develop forecasting models across near-, medium-, and long-term horizons.
• Build insights using advanced statistical modeling, causal inference, and analytics on large datasets.
• Create simulation and scenario-analysis capabilities for patient, payer, provider, and market dynamics.
• Deliver end-to-end modeling lifecycle including scoping, prototyping, data analysis, feature engineering, deployment, monitoring, and explainability.
• Collaborate with Commercial, Operations, Finance, and Technology to integrate forecasts into business workflows.
• Research and evaluate emerging forecasting, data science, and AI tools and methods for business problems.

What you'll need

• 8+ years of experience applying data science in enterprise environments delivering business value.
• Expertise in time-series forecasts, probabilistic programming, Bayesian and predictive modeling.
• Strong Python and SQL skills.
• Experience with tools/libraries including scikit-learn, PyMC, Pytorch, Tensorflow, and other data science libraries.
• Analytical and statistical intuition for novel insights from messy, complex datasets (e.g., latent variable modeling, high-dimensional clustering, causal inference, quasi-experimental methods).
• Strong communication and story-telling skills for translating technical concepts to non-technical stakeholders.
• Strong collaboration skills to work effectively cross-functionally.