Senior Scientist - Translational Safety & Risk Sciences; TSRS

Join Amgens Mission of Serving Patients At Amgen, if you feel like youre part of something bigger, its because you are. Our shared missionto serve patients living with serious illnesses drives all that we do. Since 1980, weve helped pioneer the world of biotech in our fight against the worlds toughest diseases. With our focus on four therapeutic areas Oncology, Inflammation, General Medicine, and Rare Disease we reach millions of patients each year.

Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, youll 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, youll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Lets do this. Lets change the world. In this vital role you will lead efforts to develop and integrate modern data infrastructure, analytics platforms, and visualization capabilitiestosupport New Approach Methodologies(NAMs) and broader translational safety initiatives across the organization. This role sits at the intersection ofdiscovery biology,nonclinical safety,NAMs,and translational medicine, requiring strong technicalexpertisecombined with scientific curiosity andthe ability to collaborate cross-functionally. You will partner closely with scientistsacross Amgenand data engineering groups todevelop ascalable, connected, and insight-driven data ecosystemsfor NAMs, upon which AI/ML can be applied,thatwillaccelerate decision-making across

Amgen Research.

Although this position sits within TSRS, the position will have a Research-wide reach.

• Design, develop, andmaintainscalable data infrastructure and visualization solutions supporting NAMs initiative sand other TSRS workflows
• Develop and implement databasesand registries using tools such as Databricks
• Collaborate with cross-functional partners, including scientific, data engineering, IT, and AI/ML teamsto 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 dashboardsandvisualizationsusing platforms such as Spotfireto enableAI-supported anddata-driven decision-making
• Translate complex scientific and technical concepts into clear visualizations and actionable insights for diverse stakeholders
• Develop pipelines and workflows tointegrateNAMs dataand 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

We are all different, yet we all use our unique contributions to serve patients. The Senior Scientist we seek is a researcher with these qualifications.

• Doctorate degree PhD
• PharmD
• MD [and relevant post-doc where applicable]
• Masters degree and 3 years of Scientific and/or Data Science experience
• Bachelors degree and 5 years of Scientific and/or Data Science experience

• Experience developing data infrastructure and analytics solutions in Databricks environments
• Knowledge of relational databases, data engineering workflows, and cloud-based analytics platforms
• Strongexpertisein 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 datasetsand otherstructuredorunstructuredinternal and external/publicdatasets
• Experience defining data models for complex biological entities such as NAMs and advanced model systems, includingdisease-relevantmodels, 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 oftarget 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 teamsand activelyidentifyopportunities to link people, models, datasets, tools,…