Advisor, Data Scientist - CMC Data Products

Eli Lilly and Company is a pharmaceutical company focused on discovering and delivering life-changing medicines. The company is seeking an Advisor, Data Scientist to develop enterprise-scale data products that support AI-driven insights, process optimization, and regulatory compliance across CMC, PAT, and analytical workflows. The role also leads data standardization, integration, governance, and cross-functional collaboration across pharmaceutical R&D and manufacturing.

What you'll do:

• Data Product Development: Define the roadmap and deliver analysis-ready and AI-ready data products that enable AI/ML applications, PAT systems, near-time analytical testing, and process intelligence across CMC workflows
• Data Archetypes & Modern Data Management: Define pharmaceutical-specific data archetypes (process, analytical, quality, CMC submission) and create reusable data models aligned with industry standards (ISA-88, ISA-95, CDISC, eCTD)
• Modern Data Management for Regulated Environments: Implement data frameworks that ensure 21 CFR Part 11, ALCOA+, and data integrity compliance, while enabling scientific innovation and self-service access
• AI/ML-ready Data Products: Build training datasets for lab automation, process optimization, and predictive CQA models, and support generative AI applications for knowledge management and regulatory Q&A
• Cross-Functional Leadership: Collaborate with analytical R&D, process development, manufacturing science, quality, and regulatory affairs to standardize data products
• Scalable data integration platform that automates compilation of technical-review-ready and submission-ready data packages with demonstrable quality assurance
• Unified CMC data repository supporting current process and analytical method development while enabling future AI/ML applications across R&D and manufacturing
• Data flow frameworks that enable self-service access while maintaining GxP compliance and audit readiness
• Comprehensive documentation, standards, and training programs that democratize data access and accelerate product development

What they're looking for:

• PhD in Computer Science, Data Science, Machine Learning, Biomedical / Medical Informatics, Computational Biology, AI, or closely related STEM degree and 0-5 years of pharmaceutical industry experience; or
• Master of Science in Computer Science, Data Science, Machine Learning, AI, Computational Biology, Biostatistics / Applied Statistics / Statistics, or closely related STEM degree and 5+ years of pharmaceutical industry experience
• Knowledge of modern data stack technologies (Microsoft Fabric, Databricks, Airflow) and cloud platforms (AWS- S3, RDS, Lambda/Glue, Azure)
• Demonstrated experience designing data products that support AI/ML workflows and advanced analytics in scientific domains
• Proficiency with SQL, Python, and data visualization tools
• Experience with analytical instrumentation and data systems (HPLC/UPLC, spectroscopy, particle characterization, process sensors)
• Knowledge of pharmaceutical manufacturing processes, including batch and continuous manufacturing, unit operations, and process control
• Expertise with data modeling for time-series, spectroscopic, chromatographic, and hierarchical batch/lot data
• Experience with laboratory data management systems (LIMS, ELN, SDMS, CDS) and their integration patterns
• Understanding of Design of Experiments (DoE), Quality by Design (QbD), and process validation strategies
• Experience implementing data mesh architectures in scientific organizations
• Knowledge of MLOps practices and model deployment in validated environments

Benefits:

• Company bonus (depending, in part, on company and individual performance)
• 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
• Well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities)
• Employee resource groups (ERGs) offer strong support networks for their members and are open to all employees.