Scientific Lead, Molecular Characterization

100 Eli Lilly and Company; New York (NY); On-site; USD 138,000 - 224,000; Full time

Benefits offered by this job

401(k) matching

Pension

Vacation benefits

Medical/Dental/Vision benefits

Flexible benefits

Life insurance

Well-being programs

Job summary

Lilly is seeking a Scientific Lead in spatial biology to architect and scale spatial transcriptomics platforms for Oncology discovery. You will drive end‑to‑end workflows, collaborate with informatics, histology, and project teams, and mentor junior scientists to advance platform maturity.

The role requires hands‑on experimentation, evaluating new technologies, and delivering actionable biology through robust data generation and analysis.

Qualifications

• PhD in molecular biology, genomics, genetics, or closely related discipline with 3+ years hands-on research or platform development.
• Deep hands-on expertise in spatial transcriptomics platforms (Visium HD, CosMx, Xenium).
• Working knowledge of spatial data analysis tools and image analysis platforms for tissue-based data.

Responsibilities

• Design and lead development of spatial transcriptomics workflows and end‑to‑end data generation.
• Integrate spatial transcriptomics with spatial proteomics and single-cell data.
• Develop tissue processing standards for diverse sample types to maximize data quality.
• Create image analysis pipelines for tissue segmentation and cell-type deconvolution.
• Evaluate emerging spatial technologies and translate into internal capabilities.

Skills

Spatial transcriptomics

Python/R scripting

Single-cell integration

Image analysis

Education

PhD in molecular biology/genomics

Tools

Visium HD

CosMx

Xenium

QuPath

HALO

Seurat

Squidpy

Scanpy

Job description

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life‑changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us. At Lilly, we unite caring with discovery to help make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life‑changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

Position Summary

The Scientific Lead position would be the principal architect for spatial biology within the Molecular Characterization team in Discovery Technologies, responsible for developing, optimizing, and scaling these platforms in support of Oncology drug discovery at Lilly. The Molecular Characterization team sits at the intersection of genomics, proteomics, and emerging molecular technologies, providing cutting‑edge platform capabilities across Lilly's discovery portfolio. The central mandate is invention: defining what next‑generation spatial can do, and building the infrastructure to realize their full potential within the group. The successful candidate will possess deep, applied expertise in spatial transcriptomics (e.g., Visium HD, CosMx, Xenium). Of equal importance is an entrepreneurial scientific mindset, a genuine drive to evaluate and deploy emerging tools that have not yet been established as standard practice within the field. This is a hands‑on role where direct experimentation and platform development are central to scientific impact, with growing opportunities to shape scientific direction and mentor junior team members as the platforms mature. This position requires close collaboration with Oncology project teams, automation specialists, histology, and discovery informatics to translate novel molecular insights into actionable biology.

Key Responsibilities

• Design and lead the development of spatial transcriptomics and multi‑modal spatial workflows, encompassing tissue optimization, library construction, and end‑to‑end data generation using platforms such as Visium HD, CosMx, and Xenium.
• Drive the integration of spatial transcriptomics with complementary modalities, including spatial proteomics (e.g., CosMx protein panels, CODEX/PhenoCycler) and single‑cell data, to generate comprehensive tissue‑level molecular maps.
• Establish and continuously improve tissue processing standards for diverse sample types relevant to Oncology (FFPE, fresh‑frozen, bone marrow, cryosections), with a focus on maximizing data quality from challenging or low‑input specimens.
• Develop image analysis pipelines in collaboration with discovery informatics, including tissue segmentation, cell type deconvolution, and morphological co‑registration using tools such as QuPath, HALO, or equivalent platforms.
• Evaluate emerging spatial technologies on an ongoing basis and translate promising platforms into internal capabilities through systematic feasibility assessment and implementation planning.
• Contribute to automation of NGS and spatial library preparation protocols in collaboration with automation and histology specialists.
• Develop custom targeted panels and probe/index designs for the spatial platforms to address specific genomic and transcriptomic questions posed by Oncology project teams.
• Establish protocol QC frameworks and performance benchmarks to ensure data integrity across all high‑throughput molecular platforms.
• Apply and adapt spatial data analysis tools (e.g., Seurat, Squidpy, Scanpy) to process, visualize, and interpret spatial transcriptomics datasets in close partnership with the discovery informatics team.
• Work with bioinformaticians to design and evaluate computational workflows for long‑read data, including isoform quantification, structural variant calling, and base modification detection.
• Serve as the internal scientific authority on spatial and long‑read sequencing platforms; advise Oncology project teams on platform selection, experimental design, and interpretation.
• Provide mentorship and hands‑on coaching to junior scientists; build a team culture grounded in technical rigor, creative problem‑solving, and collaborative execution.
• Establish and manage relationships with academic collaborators, technology vendors, and contract research organizations to stay at the leading edge of platform development.
• Prepare and deliver scientific presentations, publications, and study reports to internal and external audiences.
• Maintain up‑to‑date knowledge of the scientific landscape in spatial biology, long‑read genomics, and multi‑omics; proactively share emerging opportunities with the broader team.

Required Qualifications

• PhD in molecular biology, genomics, genetics, or a closely related discipline, with 3+ years of hands‑on research or platform development experience in an academic or industry setting.
• Deep hands‑on expertise in spatial transcriptomics platforms (Visium HD, CosMx, Xenium, or equivalent), from tissue section preparation through library construction and QC.
• Demonstrated experience with tissue optimization and sample handling for spatial applications across diverse and challenging sample types (FFPE, fresh‑frozen, bone marrow, cryosections).
• Working knowledge of spatial data analysis tools (e.g., Seurat, Squidpy, Scanpy) and image analysis platforms (e.g., QuPath, HALO) for tissue‑based data.
• Proficiency scripting in Python and/or R to apply, adapt, and troubleshoot single‑cell and spatial analysis tools (e.g., Scanpy/Squidpy, Seurat).
• Demonstrated track record of building or deploying new molecular platforms or technologies, not solely operating established protocols.
• Excellent scientific communication skills; ability to convey complex results clearly to technical and non‑technical stakeholders.
• Demonstrated ability to work independently and as part of a cross‑functional team in a fast‑paced environment with evolving priorities.
• Experience with multimodal spatial platforms integrating transcriptomics and proteomics (e.g., CosMx protein, CODEX/PhenoCycler).
• Experience developing novel targeted sequencing panels, including probe design and index optimization.
• Knowledge of multi‑omics platforms such as Nanostring, Quanterix, Luminex, or Fluidigm.
• Experience processing and interpreting large‑scale biological datasets; familiarity with Spotfire or similar data visualization tools.

Additional Preferred Qualifications

• Deep hands‑on expertise in spatial transcriptomics platforms (Visium HD, CosMx, Xenium, or equivalent), from tissue section preparation through library construction and QC.
• Demonstrated experience with tissue optimization and sample handling for spatial applications across diverse and challenging sample types (FFPE, fresh‑frozen, bone marrow, cryosections).
• Working knowledge of spatial data analysis tools (e.g., Seurat, Squidpy, Scanpy) and image analysis platforms (e.g., QuPath, HALO) for tissue‑based data.
• Proficiency scripting in Python and/or R to apply, adapt, and troubleshoot single‑cell and spatial analysis tools (e.g., Scanpy/Squidpy, Seurat).
• Demonstrated track record of building or deploying new molecular platforms or technologies, not solely operating established protocols.
• Excellent scientific communication skills; ability to convey complex results clearly to technical and non‑technical stakeholders.
• Demonstrated ability to work independently and as part of a cross‑functional team in a fast‑paced environment with evolving priorities.
• Experience with multimodal spatial platforms integrating transcriptomics and proteomics (e.g., CosMx protein, CODEX/PhenoCycler).
• Experience developing novel targeted sequencing panels, including probe design and index optimization.
• Knowledge of multi‑omics platforms such as Nanostring, Quanterix, Luminex, or Fluidigm.
• Experience processing and interpreting large‑scale biological datasets; familiarity with Spotfire or similar data visualization tools.

Work Environment and Physical Demands

This position is primarily laboratory‑based. Travel requirements are less than 5%. The physical demands described are representative of those required to successfully perform the essential functions of this role. Reasonable accommodations may be made for individuals with disabilities. Company Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions.

If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).

The anticipated wage for this position is $138,000 - $224,400 Full‑time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance).

In addition, Lilly offers a comprehensive benefit program to eligible employees, including

• 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)

Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

#WeAreLilly At Lilly we strive to ensure our employees are part of a team that cares about them and our shared purpose of making life better for those around the world. How do we do this? We continue to look for ways to include, innovate, accelerate and deliver while maintaining integrity, excellence and respect for people. We hope that you seek to join us on our journey as we create medicine and deliver improved outcomes for patients across the globe! #WeAreLilly