Principal Data Scientist - Forecasting

Career Category

Information Systems

Job Description

Join Amgen’s Mission of Serving Patients

At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Principal Data Scientist - Forecasting

What you will do

We are seeking a Principal Data Scientist - Forecasting 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 Amgen’s 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

• Doctorate degree and 2 years of data science in enterprise environments experience OR

• Master’s degree and 4 years of data science in enterprise environments experience OR

• Bachelor’s degree and 6 years of data science in enterprise environments experience OR

• Associate’s degree and 10 years of data science in enterprise environments experience OR

• High school diploma / GED and 12 years of data science in enterprise environments experience

Preferred Qualifications

• 8+ 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 execu