Data Scientist- 35511

SUMMARY:
This role supports the digital transformation of Amgen Operations by leveraging advanced analytics to characterize business performance in Operations, evaluate potential opportunities, and enable step change in business performance. The role will be responsible for providing analytical support and enabling data-driven decision making that will build foundational capability to provide end -to-end visibility into business processes and build advanced analytics solutions to drive value. In addition to focusing on solving traditional and big data problems, this role will be supporting our Data Management and Governance programs, Data Architecture and Modeling, and the overall data footprint. This role will interact with a wide range of bus iness leaders to understand processes, analyze data, and present findings.

FUNCTIONS:

• Assist in cross functional analytics projects from beginning to end from building relationships with key business leaders to collecting and analyzing data, as well as summarize and present key insights in support of decision making to help evaluate strategic options that support data and analytics transformation.
• Use analytics tools and scientific rigor to produce actionable insights.
• Assist in the development of a wide range of innovative data and analytics solutions, from descriptive to machine learning based (including real-time visualization tools that leverage Big Data platforms with real-time data ingestion and processing).
• Collaborate with business leaders, subject matter experts, and decision makers to develop success criteria and optimize analytics solutions across Operations.
• Partner with business to share data best practices and support business / IS led implementation.
• Assist in developing business cases and strategic recommendations.
• Interact with various finance groups including functional FP and A to understand impact to budget/long range plans.
• Provide support in developing executive communications and present analysis and insights to Amgen’s senior leadership.
• Perform ad hoc analysis and support special projects.

EDUCATION:

• Master’s degree in Science or Engineering.
• Bachelor’s degree in Science and Engineering and 2 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field experience.
• The preferred candidate should have an educational background in Data Science.
• The following educational backgrounds may be considered, provided the candidate’s experience meets the role requirements: Industrial Engineering, Systems Engineering, Computer Science, Chemical Engineering, Biomedical Engineering, Biotechnology, Manufacturing Engineering, or a related technical discipline.
• A background in Engineering is highly preferred due to the project’s focus on resource planning, workload modeling, capacity evaluation, process optimization, and operational efficiency. However, candidates from science, or data-focused backgrounds may also be strong fits if they demonstrate experience with data analytics, digital tools, GMP operations, and validation support.

PREFERRED QUALIFICATIONS:

• The ideal candidate should demonstrate a strong combination of technical, analytical, and operational skills to support AI-enabled optimization, resource planning, and validation-related initiatives within Drug Product.
• A standout candidate would have experience or demonstrated capability in the following areas:
  • Data analytics and visualization.
  • Ability to collect, organize, clean, analyze, and interpret complex operational or manufacturing data. Experience with tools such as Excel, Power BI, Smartsheet, JMP, Minitab, or similar platforms would be highly valuable.
  • Programming, automation, and AI-enabled tools.
  • Foundational programming or automation experience, including exposure to Python, Codex, AI-assisted coding tools, Power Automate, scripting, database structure, or digital workflow development. The candidate does not need to be an expert programmer but should be comfortable learning and applying digital tools to solve business problems.
  • Statistical and process evaluation mindset.
  • Understanding of basic statistics, process variability, trending, capacity evaluation, data comparison, and performance monitoring. This would support both workload forecasting and characterization/validation data evaluation.
  • Validation and GMP documentation experience.
• Knowledge of GMP expectations, validation lifecycle activities, protocol/report development, documentation practices, data integrity, discrepancy follow-up, and compliance-driven execution. Experience supporting characterization studies, engineering runs, PPQ, or validation deliverables would make the candidate especially strong.
• Strong communication and stakeholder engagement
• Ability to work with cross-functional teams, gather user requirements, translate business needs into tool requirements, and communicate findings clearly to management and technical stakeholders.
• Be available to support non-standard shift when activities are required.

WORK METHODOLOGY:

• Full on site job in Juncos, PR
• Full time job
• Expected project duration: 6 months for the first contract with a high possibility of extension based on performance and budget.
• Administrative shift; availability to work on weekends as needed.
• Expected hiring date: August 2026