Role Description Join Amgen’s Mission of Serving Patients. In this role, you will design, build, and deploy scalable data products, dashboards, analytical models, and cloud-based data solutions that improve operational visibility, risk management, supplier performance monitoring, and business decision-making. This role will partner with External Supply stakeholders, internal manufacturing sites, contract manufacturing organizations, Supply Chain, Quality, Finance, and central information technology teams to translate business needs into trusted, actionable, and governed data solutions. The successful candidate will bring strong technical expertise in advanced analytics, data engineering, cloud data platforms, and data governance, along with working knowledge of pharmaceutical manufacturing, external supply, supply chain, finance, and procurement processes. - Design, build, and maintain data pipelines, curated datasets, analytical data products, and reporting layers using Python, SQL, and cloud-based data platforms. - Develop dashboards and visual analytics to monitor External Supply performance, manufacturing status, inventory, supply risk, supplier performance, procurement activity, and operational trends. - Apply statistical, analytical, and data science methods to identify patterns, generate insights, support scenario analysis, and improve business decision-making. - Partner with External Supply business stakeholders to define requirements, clarify business problems, identify data sources, and deliver fit-for-purpose digital and analytical solutions. - Integrate and analyze structured and non-structured data from enterprise systems, including ERP, supply planning, procurement, manufacturing, quality, finance, and external partner data sources. - Automate recurring reports and manual analyses to improve efficiency, consistency, and data accessibility. - Collaborate with information technology and business teams to design scalable, maintainable, and reusable data architecture. - Support data governance, data quality, documentation, and validation practices for analytics used in a regulated pharmaceutical environment. - Communicate analytical findings, technical recommendations, and business insights clearly to technical and non-technical audiences. - Promote best practices for code development, dashboard design, data management, analytics lifecycle management, and digital product sustainability. Qualifications - Doctorate degree - OR Master’s degree and 2 years of Data Scientist experience - OR Bachelor’s degree and 4 years of Data Scientist experience - OR Associate’s degree and 8 years of Data Scientist experience - OR High school diploma / GED and 10 years of Data Scientist experience Requirements - Experience in pharmaceutical, biotechnology, life sciences, or regulated manufacturing environments. - Strong proficiency in Python for data processing, automation, analytics, and model development. - Strong SQL skills, including complex queries, joins, aggregations, data transformation, and working with large datasets. - Experience developing dashboards or visual analytics using tools such as Tableau, Power BI, or similar platforms. - Experience with cloud databases or cloud data platforms such as Databricks, AWS, Azure, Google Cloud, or similar technologies. - Experience with data engineering processes, including ETL/ELT pipelines, data modeling, data integration, data quality, orchestration, and version control. - Experience designing scalable data models, reusable analytical datasets, and governed reporting layers. - Experience with cloud data platforms, data lake architectures, APIs, workflow orchestration tools, Git, and CI/CD concepts. - Ability to work cross-functionally with business stakeholders and technical teams to translate business requirements into analytical and digital solutions. - Knowledge of External Supply, contract manufacturing, pharmaceutical manufacturing, GMP operations, supplier management, material planning, or logistics processes. - Experience working with enterprise operation systems such as SAP, MES, LIMS, Veeva, procurement platforms, or external partner data sources. - Experience developing predictive analytics, forecasting models, optimization models, anomaly detection, machine learning solutions, or advanced statistical analyses. - Strong understanding of data governance, master data management, data lineage, documentation, and data quality practices. - Demonstrated ability to manage ambiguity, structure complex business problems, and deliver practical analytical solutions. - Strong communication, storytelling, and stakeholder engagement skills, with the ability to explain complex technical concepts to business audiences. - Ability to manage multiple priorities, work independently, and deliver high-quality results in a fast-paced, cross-functional environment. - Strong commitment to data integrity, compliance, scalability, and continuous improvement. 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. Salary Range The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is 134,168.25 USD - 181,521.75 USD. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications.