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. Data Scientist - Forecasting What You Will Do We are seeking a Data Scientist, Forecasting to join the Forecasting team within the AI & Data organization. This role will support the development of statistical, Bayesian, causal, and machine learning models that enhance forecasting capabilities and quantify uncertainty to guide decision-making across the company. This role will work cross-functionally to help build forecasting solutions that support critical business processes and contribute to Amgen’s “every patient, every time” mandate. The position is well suited to a curious and collaborative problem solver who is excited about applying forecasting methods, complex datasets, and modern analytical tools to build decision-support solutions that inform planning and business decision-making. Key Responsibilities Develop and refine statistical, Bayesian, and machine learning models to support demand forecasting across near-, medium-, and long-term planning horizons. Analyze large, complex datasets using statistical modeling, forecasting, and analytics techniques to generate insights that support business decision-making. Support the development of simulation and scenario-analysis capabilities to better understand dynamics among patients, payers, providers, and market conditions. Contribute across the modeling lifecycle, including business problem framing, exploratory data analysis, feature engineering, model development, validation, deployment support, monitoring, and explainability. Collaborate with senior team members to evaluate and apply new tools and methodologies in forecasting, data science, and AI to business problems. Communicate analytical findings and model results clearly to technical and non-technical stakeholders. Basic Qualifications Master’s degree OR Bachelor’s degree and 2 years of applying data science, analytics, or statistical modeling in industry, research, or enterprise environments experience OR Associate’s degree and 6 years of applying data science, analytics, or statistical modeling in industry, research, or enterprise environments experience OR High school diploma / GED and 8 years of applying data science, analytics, or statistical modeling in industry, research, or enterprise environments experience Preferred Qualifications 2+ years of experience applying data science, analytics, or statistical modeling in industry, research, or enterprise environments. Experience with time-series forecasting, predictive modeling, or related quantitative methods. Proficiency in Python and SQL, with experience using tools such as scikit-learn, PyMC, PyTorch, TensorFlow, or similar data science libraries. Solid analytical and statistical foundation, with the ability to work with messy and complex datasets to generate actionable insights. Familiarity with model development workflows, including data preparation, feature engineering, evaluation, and interpretation. Strong communication skills, with the ability to explain technical concepts and results to a rapplying data science, analytics, or statistical modeling in industry, research, or enterprise environments. Strong collaboration skills and ability to work effectively in cross-functional environments. Intellectual curiosity and a willingness to learn, take on ambiguous problems, and grow in a fast-paced environment Experience applying machine learning, statistical modeling, or decision science methods in retail, consumer goods, supply chain, manufacturing, or similar settings. Exposure to causal inference, probabilistic modeling, or scenario analysis is a plus. What You Can Expect Of Us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors includi