Data Scientist

Summary

Amgen is a biotechnology company focused on developing medicines for serious illnesses. The Data Scientist will support digital transformation and data-driven decision-making by developing data products, dashboards, analytical models, data pipelines, and cloud-based solutions for external supply, supply chain, quality, finance, and partner operations.

Responsibilities

• Develop, maintain, and enhance data pipelines, curated datasets, analytical data products, and reporting layers using Python, SQL, and cloud-based data platforms
• Build dashboards and visual analytics to monitor External Supply performance, manufacturing status, inventory, supply risk, supplier performance, procurement activity, and operational trends
• Apply statistical and analytical methods to identify patterns, generate insights, support scenario analysis, and improve business decision-making
• Partner with business stakeholders and senior team members to gather requirements, clarify business problems, identify data sources, and deliver fit-for-purpose analytical solutions
• Integrate and analyze structured and unstructured data from enterprise systems, including ERP, supply planning, procurement, manufacturing, quality, finance, and external partner data sources
• Automate recurring reports, data preparation activities, and manual analyses to improve efficiency, consistency, and accessibility
• Support the design and implementation of scalable, maintainable, and reusable data models and data architecture
• Support data governance, data quality, documentation, validation, and data lineage practices for analytics used in a regulated pharmaceutical environment
• Communicate analytical findings, technical recommendations, and business insights clearly to technical and non-technical audiences
• Follow best practices for code development, dashboard design, data management, analytics lifecycle management, and solution sustainability

Skills

• Master's degree
• Bachelor's degree and 2 years of Data Scientist
• Associate's degree and 6 years of Data Scientist experience
• High school diploma / GED and 8 years of Data Scientist experience
• Experience in pharmaceutical, biotechnology, life sciences, regulated manufacturing, or another complex operational environment
• Proficiency in Python for data processing, automation, analytics, and model development
• Strong SQL skills, including queries, joins, aggregations, data transformation, and working with large datasets
• Experience developing dashboards or visual analytics using 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
• Ability to work cross-functionally with business stakeholders and technical teams to translate business requirements into analytical solutions
• Knowledge of External Supply, contract manufacturing, pharmaceutical manufacturing, GMP operations, supplier management, material planning, logistics, finance, or procurement processes
• Experience working with enterprise operational systems such as SAP, MES, LIMS, Veeva, procurement platforms, or external partner data sources
• Experience developing forecasting models, predictive analytics, anomaly detection, optimization models, machine learning solutions, or advanced statistical analyses
• Understanding of data governance, master data management, data lineage, documentation, and data quality practices
• Ability to structure complex business questions and develop practical analytical solutions with guidance from senior team members
• Strong communication and storytelling skills, with the ability to explain technical concepts to business audiences
• Ability to manage multiple priorities and deliver high-quality results in a fast-paced, cross-functional environment
• Strong commitment to data integrity, compliance, scalability, and continuous improvement

Qualifications

Must Haves

• Master's degree
• Bachelor's degree and 2 years of Data Scientist
• Associate's degree and 6 years of Data Scientist experience
• High school diploma / GED and 8 years of Data Scientist experience

Nice to Haves

• Experience in pharmaceutical, biotechnology, life sciences, regulated manufacturing, or another complex operational environment
• Proficiency in Python for data processing, automation, analytics, and model development
• Strong SQL skills, including queries, joins, aggregations, data transformation, and working with large datasets
• Experience developing dashboards or visual analytics using 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
• Ability to work cross-functionally with business stakeholders and technical teams to translate business requirements into analytical solutions
• Knowledge of External Supply, contract manufacturing, pharmaceutical manufacturing, GMP operations, supplier management, material planning, logistics, finance, or procurement processes
• Experience working with enterprise operational systems such as SAP, MES, LIMS, Veeva, procurement platforms, or external partner data sources
• Experience developing forecasting models, predictive analytics, anomaly detection, optimization models, machine learning solutions, or advanced statistical analyses
• Understanding of data governance, master data management, data lineage, documentation, and data quality practices
• Ability to structure complex business questions and develop practical analytical solutions with guidance from senior team members
• Strong communication and storytelling skills, with the ability to explain technical concepts to business audiences
• Ability to manage multiple priorities 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
• 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
• Career development opportunities