Eli Lilly
Pharma · Pharma
- HQ
- Indianapolis, US
- Founded
- 1875
- Size
- 35,000+
- Website
- lilly.com
Currently tracking 36 active AI roles, up 67% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $58k–$345k (avg $175k).
| Title | Stage | AI score |
|---|---|---|
| Associate Vice President - Methods4Insight, Data Foundry Associate Vice President leading the analytical methods and computational science pillar within Data Foundry, focusing on accelerating molecule discovery. This role involves leading a team of experts in cheminformatics, computational structural biology, statistical modeling, and AI/ML, ensuring Lilly has access to advanced analytical approaches for both human scientists and AI agents. The position requires strategic decision-making on adopting or developing methods, identifying data gaps, and establishing validation frameworks, with a strong emphasis on integrating methods into AI agent workflows. | DataAgent | 8 |
| Post Doctoral Scientist – Human Genomics and Translational Data Sciences This role focuses on applying statistical and computational approaches, including machine learning, to analyze large-scale multi-omics (genomic, proteomic, metabolomic) and clinical data from biobanks and population cohorts. The goal is to identify novel therapeutic targets and biomarkers for cardiometabolic diseases. The role involves developing and implementing bioinformatics pipelines, contributing to novel statistical methods, and collaborating with interdisciplinary teams to guide therapeutic development. While the primary focus is on data analysis and method development (L0/L2), the ultimate aim is to inform drug discovery and development. |
| DataPost-train |
| 7 |
| CMC AI/ML and Automation Scientist This role focuses on applying AI/ML and automation within Chemical, Manufacturing, and Controls (CMC) disciplines in pharmaceutical R&D. The scientist will derive insights from data, build decision support tools, leverage LLMs to enhance data science workflows, and contribute to developing autonomous laboratories through AI-driven methodologies and lab automation. The primary focus is on data preparation, feature engineering, and potentially building agentic systems for experimental design and execution. | DataAgent | 7 |
| CADD Postdoctoral Scientist Postdoctoral Scientist role focused on developing synthesis-aware virtual screening workflows for early small-molecule drug discovery, integrating AI/ML with structure-based drug design and fragment chemistry. | Data | 7 |
| Computational Biologist - Quantitative Methods & Target Discovery Computational Biologist role focused on analyzing multimodal biological datasets (spatial and single-cell omics, proteomics, metabolomics, functional genomics) to advance target discovery in cardiometabolic diseases. The role involves developing predictive models, integrating diverse data types, applying AI/ML and causal inference methods, and influencing data architecture and analytical standards. Collaboration with internal AI and data engineering teams is key. | Data | 7 |
| Research Advisor - Computational Genomics This role focuses on building and maintaining production genomics infrastructure for RNA drug discovery, including data pipelines from raw sequencer output to DataLake ingestion. It also involves contributing to ML models that predict pharmacology outcomes based on sequence design and collaborating with enterprise AI teams to integrate AI/ML capabilities into RNA-specific tools. The role requires expertise in bioinformatics, high-throughput NGS data analysis, and programming, with exposure to AI/ML methods in biological sequence data. | DataPost-train | 5 |
| Director/Sr Director Pharmacometrics Director/Sr Director Pharmacometrics role at Eli Lilly focused on advancing drug discovery and development through quantitative science, with a strong emphasis on integrating AI/ML and automation into modeling workflows. The role involves scientific and technical leadership, mentoring, and shaping PMx strategy across programs and the organization, including engagement with regulatory agencies. | Data | 5 |