Senior Data Scientist

Career Category

Job Description

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.

Senior Data Scientist

What you will do

Let’s do this! Let’s change the world!

In this vital role you will be responsible for developing, maintaining, and deploying first principles and/or machine learning models for biopharmaceutical processes, including but not limited to, cell culture, biologics formulation development, and fill/finish processes. You will be responsible for model design, selection of underlying technologies and infrastructure, and ensuring successful application of models in Process Development.

The ideal candidate will have a strong background in chemical engineering or mechanical engineering as well as expertise in data science to tackle challenging cross‐functional projects. Fundamental understanding of bioprocesses as well as first principles (i.e., transport phenomena, fluid mechanics, reaction kinetics) is preferred. The candidate will be part of cross-functional project teams with frequent interactions with Amgen’s SMEs and stakeholders as well as document and communicate the underlying technical basis of the models for use by engineers and scientists.

• Design, develop, and deploy first principles, machine learning, and hybrid models to optimize biopharmaceutical processes.

• Integrate modeling software with connectivity to real-time equipment data to enable digital twins for improved process performance and understanding.

• Build and maintain robust data pipelines and agentic workflows to streamline the effort required to generate impact-level insights.

• Collaborate with cross-functional teams to translate scientific challenges into data-driven solutions and ensure seamless model integration into process development workflows.

• Champion best practices in software development, including version control, testing, and continuous integration to ensure model reliability, scalability, and reproducibility.

What we expect of you

We are all different, yet we all use our unique contributions to serve patients. The Data Sciences professional we seek is an individual with these qualifications.

Basic Qualifications:

• High school diploma / GED and 10 years of Data Sciences experience OR

• Associate’s degree and 8 years of Data Sciences experience OR

• Bachelor’s degree and 4 years of Data Sciences experience OR

• Master’s degree and 2 years of Data Sciences experience OR

• Doctorate degree

Preferred Qualifications:

• Ph.D. in Chemical Engineering, Mechanical Engineering, Applied Math, or related field

• Strong background in mechanistic modeling and first principles (e.g., transport phenomena, fluid mechanics, reaction kinetics)

• Experience in applying AI and ML algorithms to produce data-driven solutions to engineering problems

• Track record of leading modeling and data science projects

• 3+ yrs of coding experience in Python

• Understanding of biopharmaceuticals process and related unit operations

• Experience using Git for version control

• Familiarity with DevOps and software best practices (i.e., version control, continuous integration, test driven development)

• Experience with data engineering & visualization tools (e.g., Databricks, Spotfire) as well as cloud computing and data storage systems such as AWS

• Experience leveraging AI tools to generate agentic solutions for scientific workflows

• Independent, self‐motivated, organized, and able to multi‐task in time‐sensitive environments

• Excellent communication skills (written and verbal)

• Strong analytical