Principal Scientist - Data Foundry Scientific Developer

Role Summary

Principal Scientist - Data Foundry Scientific Developer. The Scientific Systems group within the Data Foundry is seeking a talented scientific programmer to join our dynamic team. This role bridges the gap between laboratory science and computational innovation, building fit-for-purpose data infrastructure and analytical pipelines that drive scientific discovery. This role will collaborate with foundational platforms and partner with Tech@Lilly and the Advanced Intelligence team (AI@Lilly) to ensure project data and software solutions are fully leveraged to facilitate scientific innovation and decision-making across the portfolio.

Responsibilities

• Design, develop, and maintain data retrieval, cleaning, and processing pipelines for complex scientific datasets
• Collaborate with multidisciplinary teams to translate scientific requirements into technical solutions
• Implement scalable computational workflows for chemistry and biology research applications
• Develop and optimize software tools and automation scripts to enhance research productivity
• Ensure data integrity, quality control, and reproducibility across scientific computing systems
• Participate in agile development cycles with iterative improvement and rapid prototyping
• Document technical processes and provide training support to research teams

Qualifications

• Required: BS/MS in Chemistry, Biology, Biochemistry, Computational Biology, Cheminformatics, Computer Science or related field with 5+ years scientific programming experience, with understanding of experimental data types and workflows
• Required: Proficiency in multiple programming languages including Python, RESTful API, Java, C#, and SQL and strong scientific prototyping/scripting
• Required: Pharmaceutical and/or Biotech Research Industry Experience

Preferred Qualifications

• Python back-end or web development experience
• Hands-on experience with cheminformatics systems such as RDKit, Schrödinger Suite, or MOE
• Experience with integration of Benchling functions
• Experience with scientific data standards and ontologies
• Knowledge of cloud computing platforms (AWS, Azure, GCP)
• Familiarity with version control systems (Git) and CI/CD practices
• Experience with data visualization and analysis tools
• Background in machine learning or statistical modeling for scientific applications
• Experience with Linux environments and bash scripting
• Familiarity with agile methodologies and collaborative development practices
• Strong learning agility and willingness to adopt new technologies
• Excellent interpersonal and communication skills with a track record of effective scientist engagement