Principal Data Scientist What you will do

We are seeking a Principal Data Scientist to join the Forecasting team, within the AI Data organization. This role will lead the development of advanced statistical, Bayesian, causal, and machine learning models that improve forecasting capabilities and quantify uncertainty to guide strategic decision making across the company.

This leader will partner across Commercial, Operations, Supply Chain, Manufacturing, Finance, and Technology to build forecasting technology that support critical business processes, ensuring Amgen delivers on its every patient, every time mandate. The role is particularly suited to a creative problem solver who is excited about leveraging state of the art forecasting methods, complex high-dimensional data sources, and agentic development practices to build decision-support tools that connect demand signals with supply constraints, enabling reliable, risk-adjusted scenario planning across short-, mid-, and long-range horizons.

Key Responsibilities

Develop advanced statistical, Bayesian, and machine learning models to forecast demand across multiple horizons, including near-, medium-, and long-term planning horizons.
Work with large, complex data sets, leveraging state of the art techniques in statistical modeling, causal inference and analytics to generate insights that support strategic decision making across the business.
Develop high fidelity simulation and scenario evaluation capabilities to understand the complex dynamics between patients, payers and providers.
Own the end-to-end modeling lifecycle, including scoping, prototyping, data analysis, feature engineering, model development, deployment and, monitoring as well as explainability.
Architect and develop self-service forecasting tools and platforms, ensuring leadership can act on near real-time predictions.
Collaborate with cross functional teams in Commercial, Operation, Finance and Technology to ensure forecasts are well integrated into critical business workflows.
Develop a holistic understanding of Amgens systems and processes in relation to industry challenges and broader trends to identify opportunities and risks.
Research and evaluate emerging tools and methodologies in forecasting, data science and AI.
Establish forecasting as an advanced, rigorous practice across the organization and upskill and mentor junior team members.

Basic Qualifications

Bachelors degree and 12 years of data science in enterprise environments experience OR
Associates degree and 14 years of data science in enterprise environments experience OR
High school diploma / GED and 16 years of data science in enterprise environments experience

Preferred Qualifications

12+ years of experience applying data science in enterprise environments with demonstrated principal-level influence or equivalent depth of expertise.
Deep expertise in time-series forecasting, probabilistic programming, Bayesian and predictive modeling, with practical experience delivering models that drive business measurable value.
Expert understanding of Python, SQL and tools such as scikit-learn, PyMC, Pytorch, Tensorflow and other data science libraries.
Strong communication and story-telling skills, with ability to explain complex technical concepts and influence executive level decision making.
Exceptional stakeholder management with ability to drive alignment on relationships, and metrics, and communicate tradeoffs clearly.
An intellectually curious self-starter who can take ambiguous problems and build robust solutions from 0 to 1.
Experience building and scaling forecasting platforms for biotech/pharma use cases and knowledge of healthcare commercial concepts such as payer/provider dynamics, formulary access, and coverage.
Experience leveraging machine learning, operations research algorithms, and statistical modeling for retail, consumer goods, supply chain or manufacturing applications
Deep expertise in causal inference, Bayesian forecasting, and hierarchical or multi-level forecasting methods.
Familiarity with ML Ops, CI/CD, and engineering best practices that enable scalable deployment and adoption of forecasting products.

Principal Data Scientist

Job Description

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