Senior Data Scientist
Amgen
4 hours ago
Remote friendly (United States)
United States
IT
Senior Data Scientist (Forecasting)
Key Responsibilities
- Develop advanced statistical, Bayesian, and machine learning models to forecast demand across multiple horizons (near-, medium-, and long-term planning).
- Work with large, complex datasets using state-of-the-art statistical modeling, causal inference, and analytics to generate insights for strategic decisions.
- Develop simulation and scenario-analysis capabilities to understand dynamics among patients, payers, providers, and market conditions.
- Perform the end-to-end modeling lifecycle (scoping, prototyping, data analysis, feature engineering, model development, deployment and monitoring) including explainability.
- Collaborate cross-functionally with Commercial, Operations, Finance, and Technology to integrate forecasts into critical business workflows.
- Research and evaluate emerging tools and methodologies in forecasting, data science, and AI for business applications.
Basic Qualifications (Required)
- Doctorate degree; OR
- Master’s degree and 2 years of applying data science in enterprise environments experience; OR
- Bachelor’s degree and 4 years of applying data science in enterprise environments experience; OR
- Associate’s degree and 8 years of applying data science in enterprise environments experience; OR
- High school diploma/GED and 10 years of applying data science in enterprise environments experience.
Preferred Qualifications
- 6+ years of applying data science in enterprise environments with demonstrated delivery of business value.
- Expertise in time-series forecasts, probabilistic programming, Bayesian and predictive modeling.
- Strong knowledge of Python and SQL; experience with scikit-learn, PyMC, Pytorch, Tensorflow, and other data science libraries.
- Strong analytical/statistical intuition (e.g., latent variable modeling, high-dimensional clustering, causal inference).
- Strong communication and ability to translate technical concepts to non-technical stakeholders.
- Strong collaboration skills; effective cross-functional work.
- Self-starter able to build solutions from ambiguous problems.
- Experience with biotech/pharma forecasting and healthcare commercial concepts (payer/provider dynamics, formulary access, coverage).
- Experience applying machine learning, statistical modeling, and decision science in retail/consumer goods/supply chain/manufacturing.
Benefits (if eligible; explicitly stated)
- Comprehensive employee benefits package (Retirement and Savings Plan with company contributions, group medical/dental/vision, life and disability insurance, flexible spending accounts)
- Discretionary annual bonus (or sales-based incentive for field sales)
- Stock-based long-term incentives
- Time-off plans
- Flexible work models (remote/hybrid where possible)
Application Instructions
- Apply via careers.amgen.com.
- No application deadline; applications will be accepted until a sufficient number are received or a candidate is selected.
Key Responsibilities
- Develop advanced statistical, Bayesian, and machine learning models to forecast demand across multiple horizons (near-, medium-, and long-term planning).
- Work with large, complex datasets using state-of-the-art statistical modeling, causal inference, and analytics to generate insights for strategic decisions.
- Develop simulation and scenario-analysis capabilities to understand dynamics among patients, payers, providers, and market conditions.
- Perform the end-to-end modeling lifecycle (scoping, prototyping, data analysis, feature engineering, model development, deployment and monitoring) including explainability.
- Collaborate cross-functionally with Commercial, Operations, Finance, and Technology to integrate forecasts into critical business workflows.
- Research and evaluate emerging tools and methodologies in forecasting, data science, and AI for business applications.
Basic Qualifications (Required)
- Doctorate degree; OR
- Master’s degree and 2 years of applying data science in enterprise environments experience; OR
- Bachelor’s degree and 4 years of applying data science in enterprise environments experience; OR
- Associate’s degree and 8 years of applying data science in enterprise environments experience; OR
- High school diploma/GED and 10 years of applying data science in enterprise environments experience.
Preferred Qualifications
- 6+ years of applying data science in enterprise environments with demonstrated delivery of business value.
- Expertise in time-series forecasts, probabilistic programming, Bayesian and predictive modeling.
- Strong knowledge of Python and SQL; experience with scikit-learn, PyMC, Pytorch, Tensorflow, and other data science libraries.
- Strong analytical/statistical intuition (e.g., latent variable modeling, high-dimensional clustering, causal inference).
- Strong communication and ability to translate technical concepts to non-technical stakeholders.
- Strong collaboration skills; effective cross-functional work.
- Self-starter able to build solutions from ambiguous problems.
- Experience with biotech/pharma forecasting and healthcare commercial concepts (payer/provider dynamics, formulary access, coverage).
- Experience applying machine learning, statistical modeling, and decision science in retail/consumer goods/supply chain/manufacturing.
Benefits (if eligible; explicitly stated)
- Comprehensive employee benefits package (Retirement and Savings Plan with company contributions, group medical/dental/vision, life and disability insurance, flexible spending accounts)
- Discretionary annual bonus (or sales-based incentive for field sales)
- Stock-based long-term incentives
- Time-off plans
- Flexible work models (remote/hybrid where possible)
Application Instructions
- Apply via careers.amgen.com.
- No application deadline; applications will be accepted until a sufficient number are received or a candidate is selected.