Senior Data Scientist

Career Category

Engineering

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.

ABOUT THE ROLE

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

This senior member of the team will work cross-functionally to build forecasting solutions that support critical business processes and help Amgen deliver on its “every patient, every time” mandate. The role is particularly well suited to a creative problem solver who is excited about applying state-of-the-art forecasting methods, complex high-dimensional data sources, and modern analytical tooling to build decision-support solutions that inform multi-horizon planning and business decision-making.

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 datasets, 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 simulation and scenario-analysis capabilities to better understand the complex dynamics among patients, payers, providers, and market conditions

• Execute across the end-to-end modeling lifecycle, including scoping, prototyping, data analysis, feature engineering, model development, deployment and, monitoring as well as explainability.