Data Scientist – AI Applications Engineer

Career Category

Process Development

Job Description

Job Summary

Transformative Digital Capabilities (TDC) drives Process Development (PD) and Operations digital transformation through pragmatic digital innovation that systematically delivers for the present while also building for the future. Our mission is to empower Process Development staff to harness their transformative potential through the rapid convergence of chemistry, biology, engineering, and computing, accelerated by innovative digital capabilities. TDC's core competencies span clear thought leadership and deep domain expertise in Data Products, Artificial Intelligence, Digital Twins, Product Management, and Organizational Change Management following Scaled Agile practices.

As part of our team expansion at Amgen India (AIN), we are seeking a Level 4 AI Engineer to contribute to the development, evaluation, and deployment of AI-enabled workflow capabilities for Process Development. The successful candidate will work within defined workstreams to prepare scientific data, implement machine learning and generative AI components, test solution performance, and document results. This role will collaborate closely with senior data scientists and AI engineers, product owners, AIN colleagues, U.S. TDC partners, scientists, data strategy teams, and software/platform partners. The role requires strong hands-on execution, learning agility, clear communication, and effective collaboration across time zones.

What You Will Do

Contribute to AI-enabled use cases: work with senior data scientists, AI engineers, product owners, and scientific partners to turn defined requirements into practical data and AI workflow components for Process Development.

Prepare data and build workflow components: clean, transform, and integrate structured and unstructured scientific data and metadata, and implement retrieval, automation, context, or human-in-the-loop components using established designs and standards.

Develop and evaluate models and AI systems: implement machine learning, generative AI, retrieval-augmented generation, or decision-support approaches; prepare test data; run benchmarks; perform error analysis; and compare results against defined acceptance criteria.

Contribute to reliable software delivery: develop maintainable Python code, notebooks, scripts, pipelines, or services using team practices for version control, testing, review, documentation, and reproducibility.

Collaborate in agile product delivery: support requirements clarification, backlog refinement, implementation planning, demonstrations, user testing, feedback collection, and incremental improvement of AI-enabled capabilities.

Document and communicate results: clearly describe data sources, methods, assumptions, model or agent behavior, limitations, test evidence, and appropriate use to technical and non-technical stakeholders.

Basic Qualifications

Master's or Bachelor's degree and minimum 4 years of related experience in engineering, computer science, data science, applied mathematics, statistics, life sciences, or a related technical field

Required Skills/Experience

Hands-on programming experience in Python for data analysis, modeling, automation, or application development.

Experience preparing, cleaning, exploring, and integrating structured or unstructured data for analytical or machine learning use cases.

Experience with one or more of machine learning, generative AI, retrieval-augmented generation, workflow automation, or decision-support systems.

Experience applying standard evaluation methods, including train/test design, performance metrics, benchmark execution, error analysis, and quality checks.

Familiarity with software engineering practices such as version control, code review, testing, documentation, and reproducible workflows.

Experience with experimental data, scientific metadata, laboratory workflows, process development data, data pipelines, or data products.

Understanding of biopharmaceutical development, manufacturing science, analytical development, or another regulated technical environment.

Familiarity with cloud, data platform, API, notebook, or application development patterns used to deliver analytical capabilities.

Ability to execute well-scoped technical tasks, seek clarification when requirements are incomplete, and communicate risks or dependencies early.

Strong written and verbal communication skills and the ability to work effectively in a matrixed global environment across AIN and U.S. time zones.

Candidate Profile

The ideal candidate is a hands-on data scientist who can contribute effectively within a cross-functional delivery team. They should be comfortable preparing and analyzing scientific data, implementing scoped machine learning and AI components, testing and documenting their work, and incorporating feedback from senior technical and product partners. This role is suited to someone who wants to deepen their expertise in Process Development and grow toward broader technical ownership over time.

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation

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