Data Scientist - Forecasting

Amgen•Thousand Oaks, CA

About The Position

Amgen is seeking a Data Scientist, Forecasting to join the Forecasting team within the AI & Data organization. This role is crucial for developing statistical, Bayesian, causal, and machine learning models to enhance forecasting capabilities and quantify uncertainty, thereby guiding decision-making across the company. The Data Scientist will work cross-functionally to build forecasting solutions that support critical business processes and contribute to Amgen’s mission of serving patients. The ideal candidate is a curious and collaborative problem solver eager to apply forecasting methods, complex datasets, and modern analytical tools to inform planning and business decisions.

Requirements

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
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.
Strong communication skills, with the ability to explain technical concepts and results to technical and non-technical stakeholders.
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.

Nice To Haves

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.
Familiarity with model development workflows, including data preparation, feature engineering, evaluation, and interpretation.
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.

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.

Benefits

Competitive benefits
Collaborative culture
Professional and personal growth and well-being support
Comprehensive employee benefits package
Retirement and Savings Plan with generous company contributions
Group medical, dental and vision coverage
Life and disability insurance
Flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible