Process Engineering Data Scientist

Eli Lilly and CompanyCarolina, PR
11dOnsite

About The Position

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. Organization Overview The Process Engineering function is part of the Engineering Department and provides technical expertise and support to Dry Product Operations (DPO). The team ensures compliance with cGMP and HSE guidelines, regulatory requirements, company standards, and business practices. Primary areas of support include technical expertise (process and equipment), manufacturing and business process improvements, compliance with business systems, and talent development. DPO technologies and processes include Wet Granulation, Roller Compaction, Tablet Compression/Coating/Inspection/Printing, Direct Compression Continuous Manufacturing, and Capsule Filling/Inspection. Responsibilities As a Process Engineering Data Scientist at Lilly del Caribe, Inc., Carolina, Puerto Rico, you will analyze complex data sets, automate process-monitoring programs, develop predictive models, conduct multivariate analysis, leverage generative AI, and identify insights that drive business decisions. You will collaborate with cross-functional teams across the enterprise to understand business challenges, develop hypotheses, and validate those hypotheses with data.

Requirements

  • Ph.D. in Engineering preferred, or Bachelor’s/Master’s degree in Engineering with at least 5 years of experience in data analysis and digitalization.
  • 5+ years of experience in pharmaceutical manufacturing operations.
  • Bilingual (English/Spanish) with strong written and verbal communication skills.
  • EIT license required at a minimum (CIAPR membership).
  • Experience with machine learning algorithms and statistical modeling.
  • Proficiency in programming languages.

Nice To Haves

  • Strong analytical and problem‑solving skills.
  • Excellent communication and attention to detail.
  • Strong leadership and organizational capabilities.
  • Basic to intermediate knowledge of oral solid dosage pharmaceutical manufacturing operations (highly desirable).
  • Ability to work with diverse data sources and data types.
  • Familiarity with data visualization tools and methods.
  • Ability to thrive in a fast‑paced, collaborative environment.
  • Experience with deep learning and reinforcement learning.
  • Familiarity with cloud computing platforms.
  • Knowledge of generative AI applications.
  • Strong understanding of Automation & Control Systems.
  • Experience with data engineering and data pipeline development.
  • Strong leadership and project management skills.

Responsibilities

  • Serve as a DPO equipment/asset steward for the assigned area to maintain efficient manufacturing processes.
  • Establish and maintain technical information for manufacturing processes and unit operations.
  • Lead the deployment and sustainability of the local Engineering Digital Program.
  • Develop and implement machine learning algorithms to analyze large data sets.
  • Collaborate with cross-functional stakeholders to understand business needs and deliver data-driven solutions.
  • Communicate insights and recommendations to both technical and non-technical audiences.
  • Conduct research to identify emerging trends and technologies in data science.
  • Manage and prioritize multiple projects simultaneously.
  • Apply advanced analytics techniques to solve complex business problems.
  • Develop predictive models and automated data capture systems.
  • Enhance and sustain data monitoring programs.
  • Ensure data quality, integrity, and accuracy.

Benefits

  • Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance).
  • In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).
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