Role Summary
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 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
Skills
- Python, RESTful API, Java, C#, SQL
- Scientific programming and prototyping
- Data integration and pipeline development
- Agile development practices
- Data integrity, quality control, and reproducibility
Education
- BS/MS in Chemistry, Biology, Biochemistry, Computational Biology, Cheminformatics, Computer Science or related field
Additional Requirements
- Experience with laboratory data types and workflows is assumed; familiarity with chemistry and biology research applications preferred