Data Scientist - Forecasting
Role details
Job location
Tech stack
Job description
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 Amgens 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., * 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.
Requirements
- Masters degreeOR
- Bachelors degree and 2 years of applying data science, analytics, or statistical modeling in industry, research, or enterprise environments experience OR
- Associates degree and 6 years of applying data science, analytics, or statistical modeling in industry, research, or enterprise environments experienceOR
- High school diploma / GED and 8 years of applying data science, analytics, or statistical modeling in industry, research, or enterprise environments experience, * 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.
Benefits & conditions
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 including but not limited to, relevant skills, experience, and qualifications.
In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include:
- 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 where possible. Refer to the Work Location Type in the job posting to see if this applies.