Sr. Data Scientist

Lead advanced analytics that translate into measurable business value. In this full-time, onsite role in Juncos, PR, you will drive end-to-end data science work, collaborating across PR Operations to build analytical models and insights that help solve real business problems. You will also apply data science, machine learning, and AI capabilities across Amgen’s commercial organization, using a strong mix of technical analysis and operational thinking.

What you’ll do

• Lead, use, and develop data science, machine learning, and AI capabilities across Amgen’s commercial organization
• Take ownership of projects and partner with cross-functional teams to systematically derive insights that create substantial business value
• Work independently with minimal supervision, taking initiative from problem identification through delivery
• Identify business needs, perform SWOT analysis, propose analytical approaches, obtain approvals, and execute the work end to end
• Build high-performance algorithms, prototypes, predictive models, and proof of concepts using Python
• Use SQL and other database query languages to support analysis and model development
• Collaborate with stakeholders to define methodology for specific business questions, then communicate ideas, progress, and results clearly
• Create clear, impactful narratives in PowerPoint using the MS Office suite, including Excel and PowerPoint
• Assure compliance with regulatory, security, and privacy requirements related to data assets

Required experience and education

• Doctorate or Master’s (or equivalent related degree) plus 2 years of experience in a related field (data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science, or similar)
• Education/experience alternatives may be considered as follows:
  • Bachelor’s plus 4 years of relevant experience
  • Associates plus 8 years of relevant experience
• Relevant technical disciplines may include: Industrial Engineering, Systems Engineering, Computer Science, Chemical Engineering, Biomedical Engineering, Biotechnology, Manufacturing Engineering, or a related field
• Support for AI-enabled optimization, resource planning, and validation-related initiatives within Drug Product
• Ability to meet operational needs, including being available to support non-standard shift when required

Preferred fit areas (capabilities to bring)

• Engineering background highly preferred for resource planning, workload modeling, capacity evaluation, process optimization, and operational efficiency
• Experience or strength in data analytics and visualization, including the ability to collect, organize, clean, analyze, and interpret complex operational or manufacturing data (tools such as Excel, Power BI, Smartsheet, JMP, Minitab, or similar)
• Programming, automation, and AI-enabled tools, including foundational exposure to Python, Codex, AI-assisted coding tools, Power Automate, scripting, database structure, or digital workflow development (not required to be an expert programmer, but comfortable learning and applying digital tools to solve business problems)
• A statistical and process evaluation mindset, including basic statistics, process variability, trending, capacity evaluation, data comparison, and performance monitoring to support workload forecasting and characterization/validation data evaluation
• Validation and/or GMP documentation experience, including knowledge of GMP expectations, validation lifecycle activities, protocol/report development, documentation practices, data integrity, discrepancy follow-up, and compliance-driven execution
• Strong communication and stakeholder engagement, including translating business needs into tool requirements

Technologies you’ll work with

• Python
• SQL and DB query languages
• PowerPoint, MS Office suite (Excel, PowerPoint)
• Power BI, Smartsheet, JMP, Minitab
• Power Automate, Codex, AI-assisted coding tools, scripting

Location: Juncos, PR (onsite)

Job type: Full-time

Compensation: USD 50.00–55.00 per hour