[Hiring] Senior Scientist - Translational Safety & Risk Sciences @Amgen

Role Description

Join Amgen’s Mission of Serving Patients. In this vital role you will lead efforts to develop and integrate modern data infrastructure, analytics platforms, and visualization capabilities to support New Approach Methodologies (NAMs) and broader translational safety initiatives across the organization. This role sits at the intersection of discovery biology, nonclinical safety, NAMs, and translational medicine, requiring strong technical expertise combined with scientific curiosity and the ability to collaborate cross-functionally.

You will partner closely with scientists across Amgen and data engineering groups to develop a scalable, connected, and insight-driven data ecosystem for NAMs, upon which AI/ML can be applied, that will accelerate decision-making across Amgen Research. Although this position sits within TSRS, the position will have a Research-wide reach.

Key Responsibilities:

• Design, develop, and maintain scalable data infrastructure and visualization solutions supporting NAMs initiatives and other TSRS workflows.
• Develop and implement databases and registries using tools such as Databricks.
• Collaborate with cross-functional partners, including scientific, data engineering, IT, and AI/ML teams to harmonize and standardize data structures across nonclinical and clinical safety domains.
• Define metadata standards and ontology mappings for model systems, assays, samples, readouts, validation status, and context of use.
• Support data governance, data quality, and reproducibility best practices across TSRS platforms.
• Conceptualize, design, and build interactive dashboards and visualizations using platforms such as Spotfire to enable AI-supported and data-driven decision-making.
• Translate complex scientific and technical concepts into clear visualizations and actionable insights for diverse stakeholders.
• Develop pipelines and workflows to integrate NAMs data and other internal data with enterprise datasets, such as clinical data, via AI/ML.
• Apply AI/ML approaches to support translational safety analyses, predictive modeling, and emerging NAMs applications.

Qualifications

• Doctorate degree (PhD, PharmD, or MD) [and relevant post-doc where applicable].
• Master’s degree and 3 years of Scientific and/or Data Science experience.
• Bachelor’s degree and 5 years of Scientific and/or Data Science experience.

Requirements

• Experience developing data infrastructure and analytics solutions in Databricks environments.
• Knowledge of relational databases, data engineering workflows, and cloud-based analytics platforms.
• Strong expertise in Spotfire dashboard development and data visualization.
• Experience working with SharePoint-based scientific collaboration and data environments and integrating data across multiple platforms such as Benchling, SharePoint, Databricks, Spotfire, or other LIMS or ELN systems.
• Experience integrating heterogeneous datasets, including clinical datasets and other structured or unstructured internal and external/public datasets.
• Experience defining data models for complex biological entities such as NAMs and advanced model systems, including disease-relevant models, assays, and associated datasets.
• Strong understanding of FAIR data principles, metadata standards, controlled vocabularies, ontologies, and data governance.
• Familiarity with NAMs, complex in vitro models, translational in vitro/in silico platforms, toxicology, and/or translational safety approaches.
• Understanding of target discovery, translational biology, nonclinical safety, drug discovery, and/or drug development processes.
• Strong communication and collaboration skills with the ability to work effectively across multidisciplinary teams and actively identify opportunities to link people, models, datasets, tools, and decisions.
• Demonstrated ability to manage multiple priorities in a fast-paced scientific environment.

Benefits

• 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.