Director Chemical Engineering Data Science Jobs (NOW HIRING)

1. Leading, using and developing data science, machine learning, and artificial intelligence capabilities across Amgens commercial organization.
2. Leading the projects and be part of cross functional teams on projects and/or programs with aims to systematically derive insights that ultimately derive substantial business value for Amgen.
3. Taking the initiative and work independently with minimal supervision.
4. Identifying business needs, doing SWOT analysis, proposing potential analytical approaches for solutions, obtain approvals and the execute the work end to end.
5. Building high-performance algorithms, prototypes, predictive models and proof of concepts using Python.
6. Working with SQL and other DB query languages.
7. Leading, collaborating and communicating cross-functionally with stakeholders to develop appropriate methodology to answer specific business questions.
8. Presenting analysis ideas, progress and results to business partners in clear and impactful manner.
9. Creating powerful stories in PowerPoint. Well versed in MS Office suite specifically Excel and PowerPoint.
10. Assuring compliance with regulatory, security, and privacy requirements as it relates to data assets.

• Doctorate or Masters + 2 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field experience.
• Bachelors + 4 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field experience.
• Associates + 8 years of data science, business, statistics, data mining, applied mathematics,  business analytics, engineering, computer science or related field experience.
• High school/GED + 10 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field experience.
• 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.

• 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/or GMP documentation experience.
• 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.
• 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.

SKILLS:

1. Degree in Data Science, Engineering, Mathematics, Applied Physics, Statistics, or Operations Research.
2. Experience leading the projects and in executions of the projects end to end.
3. Experience with databases including relational, SQL, and Graph.
4.  Programming experience with Python, R, or SAS and experience with ML libraries like scikitlearn, MLib, Keras, TensorFlow, Pytorch, etc.
5.  Write well-abstracted and reusable code in Python, R, or Scala; you freely navigate in Linux environment.
6. Detail-oriented technical aptitude with strong logical, problem solving, and decision-making skills.
7. Excellent organization/planning skills and talent for managing many large and complex datasets.
8. Ability to collaborate and influence business partners and other IS resources to drive analytic projects end-to-end.
9. Excellent communication skills to communicate analysis in a clear, precise, and actionable manner
10. Experience working with large datasets, experience working with distributed computing tools (Spark, Hive, etc.).
11. Passion for learning and staying on top of current developments in advanced analytics.
12. Biotech / Pharma experience.

• Full- time job
• Full on-site job
• Location: Juncos, PR
• Expected hiring month: September 2026
• Initial contract term: 6 months for the first contract with a high possibility of extension based on performance and budget.
• Number of openings: 1
• Administrative Shift (weekends and overtime may also be required).
• Professional services contract