The Diabetes, Obesity and Complications Therapeutic Area (DOCTA) at Eli Lilly and Company focuses on new treatments for diabetes, obesity, and cardiometabolic diseases. From an idea, we collaborate with partners across Lilly to discover and develop novel biologic, small molecule, and nucleic acid-based therapies. Our focus is on the patient: by understanding the biology and pathophysiology of diseases, we aim to address the root cause and develop breakthrough therapies. We have one of the strongest pipelines in the industry and a track record of delivering impactful medicines that improve lives.

The Computational Biology Lead will be the primary computational business partner for research teams within DOCTA. This includes groups focused on obesity, diabetes, heart failure, cardiovascular, and metabolic complications. The successful candidate will understand the scientific needs of each partner group. They will identify areas where computational biology can advance scientific programs. They will also ensure prompt and transparent bioinformatics support for incoming requests. Additionally, the Computational Biology Lead will manage a team of computational scientists. They will provide scientific leadership in computational biology and bioinformatics.

Are you looking for a unique opportunity to lead the use of advanced computational tools in a dynamic research field? Apply today to join the Lilly Team!

Scientific Leadership

• Provide leadership in design and execution of studies using omics-related data sources, including RNA-seq, spatial transcriptomics, single-cell omics, proteomics, and metabolomics; integrate standard and emerging AI/ML models as appropriate
• Attend disease-area and technical scientific conferences to stay up-to-date on current technical and scientific advances; ensure these current practices are being implemented within the team
• Implement industry-standard standard processes for scientific project documentation
• Hands-on execution of computational biology projects, including implementing and performing code review practices within the team and across other teams within the Data Sciences and Computational Biology (DSCB) group
• Partner with human genetics scientists within the DSCB team to design and implement integrated genotype-phenotype analyses
• Closely partner with the computational platforms and data architecture leads to within DSCB to develop innovative scientific studies and ensure scalable cross-group data and pipeline interoperability

Business Partner

• Serve as the primary point person for all inbound bioinformatics and computational biology requests from the research groups within DOCTA
• Understand DOCTA pipeline needs and proactively identify areas where computational biology can advance our scientific and early clinical programs
• Build strong relationships across DOCTA research groups; if not located in Indianapolis, regular travel to meet with Indianapolis-based research groups is required

Group Management

• Provide scientific mentorship to a team of in-house computational biologists and bioinformaticians
• Effectively delegate across team members, including in-house scientists, contractors, and vendors; identify and contract with specialty resources when necessary
• Ensure prompt, accurate, and transparent delivery of computational research projects
• Identify scientific and leadership growth opportunities for team members; ensure team members are developing skills in industry-standard and ground breaking tools

Key Requirements:

• Ph D or equivalent in Computational Biology, Bioinformatics, Biomedical Informatics, or related field
• 5+ years of industry experience post-Ph D

Additional preferences:

• 3+ years of experience managing Ph D-level direct reports required; prior industry management experience strongly preferred
• Prior experience managing bioinformatics vendors and contractors
• Prior experience with implementation and maintenance of industry-standard documentation practices including Git, Confluence, JIRA, or equivalent
• Strong track record of execution of computational biology and/or bioinformatics-based projects, potentially including RNA-seq, metabolomics, multi-omics, human genetics, proteomics, AI/ML, and other related research modalities
• Proficiency in programming languages such as R and/or Python
• Ability to prioritize and manage multiple competing priorities within a fast-paced environment
• Strongly team-oriented with a customer focused design thinking approach
• Prior experience in a metabolism-related field, including obesity, diabetes, MASH, cardiometabolic, renal, and/or related area, required