Principal Data Scientist - Optimization

Amgen • Thousand Oaks, CA

1d • Hybrid

About The Position

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. We are seeking a Principal Data Scientist, Optimization to join the Forecasting team, within the AI & Data organization. This role will lead the development, validation and deployment of advanced optimization models and decision-support solutions to guide strategic and operational decisions and help Amgen delivers on its “every patient, every time” mandate. This leader will partner across Commercial, Operations, Supply Chain, Manufacturing, Finance, and Technology to transform Amgen’s approach to operational decision making through rigorous analytical methods. The role is particularly well suited to a creative problem solver with deep expertise in mathematical optimization, including linear, nonlinear and mixed-integer programming, who is excited about applying these methods to hard problems in multi-echelon supply chain design, capacity allocation, and pricing/trade-off optimization.

Requirements

• 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
• 8+ years applying operations research, data science or machine learning algorithms in an enterprise environment with demonstrated principal-level influence or equivalent depth of expertise.
• Deep expertise in mathematical optimization including linear, non-linear, and mixed-integer programming, constrained optimization and scenario-based optimization.
• Demonstrated experience building and deploying models that drive measurable business value in areas such as supply chain, manufacturing, logistics, pricing, or resource allocation.
• Strong understanding of Python, SQL, with hands-on experience using frameworks such as Pyomo, PuLP, OR-Tools, Gurobi or equivalent.
• Strong communication and story-telling skills, with demonstrated ability to simplify complex concepts and influence executive decision making.
• Exceptional stakeholder management skills that can drive alignment on , relationships, and metrics, and communicate tradeoffs clearly.
• An intellectually curious self-starter who is able to take ambiguous problems and build robust solutions from 0 to 1

Nice To Haves

• Experience building and scaling optimization platforms or decision-support systems for biotech, pharma, healthcare, manufacturing, retail, or consumer goods applications.
• Familiarity with stochastic optimization, robust optimization, simulation-optimization, decomposition methods, heuristics, or metaheuristics for large-scale decision problems.
• Exposure to reinforcement learning or approximate dynamic decisioning methods.
• Knowledge of healthcare or biotech commercial concepts, including payer/provider dynamics, formulary/coverage considerations, or launch planning constraints

Responsibilities

• Design, build and deploy optimization models using linear, nonlinear and mixed integer programming techniques to support high value business decisions.
• Develop optimization solutions for challenging supply chain and commercial problems such as capacity allocation, supply planning, inventory optimization, portfolio tradeoffs, and price / margin optimization.
• Partner with forecasting, simulation, and analytics teams to incorporate uncertainty, demand scenarios, and operational variability into optimization-based decision frameworks.
• Own the end-to-end modeling lifecycle, including problem framing, prototype development, data analysis, model formulation, calibration, validation, testing, deployment, monitoring, and model explainability.
• Architect and develop decision-support tools and self-service applications that enable business leaders to evaluate tradeoffs and respond rapidly to changing market and operational conditions.
• Collaborate with cross-functional teams in Commercial, Operations, Finance, and Technology to ensure optimization solutions are integrated into critical business workflows and planning processes.
• Develop a holistic understanding of Amgen’s systems and processes in relation to industry challenges and broader trends to identify opportunities and risks.
• Evaluate emerging methods in optimization, reinforcement learning, and AI, and assess where they can complement classical operations research approaches.
• Establish optimization as a rigorous, scalable capability across the organization, while mentoring junior team members and setting standards for technical excellence.

Benefits

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and 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, including remote and hybrid work arrangements, where possible

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Number of Employees: 5,001-10,000 employees