Senior Data Scientist(Data & Analytics) - Python

Career Category

Process Development

Job Description

How might you defy imagination?

At Amgen, our shared mission to serve patients drives all that we do. In this vital role, you will join Amgen's Transformative Digital Capabilities (TDC) organization within Process Development and help accelerate digital transformation through analytics, data products, and AI-enabled solutions.

What will you do

As a Data Scientist, you will partner with scientists, engineers, business stakeholders, and technology teams to unlock the value of Process Development data. You will lead analytical initiatives that improve decision-making, increase data accessibility and usability, and enable scalable digital and AI capabilities across Process Development. You will work across a range of initiatives spanning data strategy, advanced analytics, process optimization, digital products, and data science solutions that improve business outcomes and accelerate innovation.

A successful candidate will independently manage multiple assignments, anticipate and prevent potential problems, develop practical solutions aligned to operational objectives, and provide guidance to other professionals.

Job Requirements

- Partner with stakeholders to identify and prioritize opportunities where analytics, AI, or data science can drive measurable value.

- Lead the design and development of analytical solutions, dashboards, models, and data products that support scientific and business decision-making.

- Apply statistical, machine learning, and data science methods to solve complex business and scientific problems.

- Drive exploratory analysis, trend analysis, forecasting, and modeling using multiple sources of data.

- Contribute to the development and deployment of AI-enabled solutions, including machine learning and generative AI use cases where appropriate.

- Improve data accessibility, usability, quality, and stewardship in partnership with data, product, and engineering teams.

- Translate business problems into analytical approaches, define success metrics, and communicate recommendations to technical and non-technical audiences.