Principal Data Scientist

• 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

Bachelor's degree and 12 years of data science in enterprise environments experience OR Associate's 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

• 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

• Retirement and Savings Plan with generous company contributions
• Group medical, dental and vision coverage
• Life and disability insurance
• Flexible spending accounts
• Discretionary annual bonus program
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models, including remote and hybrid work arrangements, where possible