H-1B Visa Bioinformatics Jobs
Bioinformatics roles sit squarely within H-1B visa specialty occupation requirements, as the work demands at minimum a bachelor's degree in computational biology, bioinformatics, or a closely related field. Pharma, biotech, and academic medical centers are consistent H-1B sponsors for these positions, filing LCAs under SOC codes that include biological scientists and computer occupations.
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Get Access To All JobsAt Lilly, we unite caring with discovery to 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 Human Genomics and Translational Data Sciences team within Cardiometabolic Research Data Science is hiring a Bioinformatics Pipeline Engineer to help build, solidify, and scale the analytical pipelines our scientists rely on every day. Our work spans multiple omics workflows, including target discovery and target due diligence, single cell sequencing, genomics, proteomics and, increasingly, AI-assisted workflows that pull these analyses together into faster, more reproducible products for therapeutic area partners across Lilly Research Labs.
This role sits at the intersection of two worlds. On one side, we employ classical bioinformatics and statistical genetics pipelines — the kind of robust, reproducible, well-tested workflows that turn messy public and proprietary genomics data into trustworthy answers. On the other, the rapidly evolving stack of AI tooling — large language models like Claude, agentic workflows, building AI-friendly connectors like MCP (Model Context Protocol), and the code that lets scientists query complex datasets in natural language. We want someone who is genuinely curious about both, and keen to use both to improve the value we derive from our datasets to enable target support and novel target discovery.
You will not be expected to be a senior expert in either domain on day one. You will be expected to bring strong software engineering instincts, and a keen curiosity and creativity to enhance the value of the tools and datasets at our disposal. You will work closely with statistical geneticists, computational biologists, and other engineers — both within our team and across Lilly — to ship tools that make the science faster and more reliable.
Key Responsibilities
Pipeline Development and Engineering
- Support for computational biology workflows, including single cell, spatial, and other multi-omics analysis workflows for clinical and preclinical applications
- Use modern workflow managers (e.g. Nextflow, Snakemake, or similar) and containerization (Docker, Singularity) to make pipelines portable, testable, and reusable across projects and teams
- Help build and maintain reproducible analytical pipelines for statistical genetics and bioinformatics workflows
- Wrap and harden ad-hoc analytical scripts written by scientists into production-quality tools that can be re-run reliably by others
- Write tests, documentation, and clear examples so the pipelines you build are usable by colleagues with a range of technical backgrounds
AI-Enabled Tooling and Workflows
- Prototype agentic workflows that automate established and routine analytical tasks — for example, pulling target evidence across data sources, generating standardized due-diligence reports, or letting scientists interrogate complex datasets in natural language
- Build and maintain MCP connectors that expose internal data, public resources, and analytical pipelines to LLM-based agents and tools like Claude
- Identify and develop use cases where LLMs and agentic AI workflows can improve the speed, quality, consistency, or accessibility of work across therapeutic areas, focusing on end-to-end capabilities rather than isolated task completion
- Contribute to a shared library of reusable AI tooling, prompt patterns, and integration code that the team can build on. Define technical standards for evaluation, documentation, guardrails, and workflow quality so that AI-based solutions are trusted, reproducible, and suitable for repeated use across teams and projects
- Know the latest with the AI tooling landscape and bring back ideas the team can put to work. Help improve AI fluency among collaborators by demonstrating practical workflows
Collaboration Across Lilly Research Labs
- Partner closely with statistical geneticists, computational biologists, and software engineers within the Cardiometabolic Data Science group and across other Lilly Research Labs teams
- Work with therapeutic area partners to understand their analytical needs and translate them into pipeline requirements
- Coordinate with platform and engineering groups to ensure your pipelines integrate cleanly with broader Lilly infrastructure
- Contribute to internal knowledge sharing — code reviews, demos, documentation, and helping colleagues get unblocked
Basic Requirements
- B.S. in computer science, computational biology, bioinformatics, biological sciences, statistics, or a related field, with 10+ years relevant work experience,
- OR M.S. in computer science, computational biology, bioinformatics, biological sciences, statistics, or a related field, with 7+ years relevant work experience
- OR Ph.D. in computer science, computational biology, bioinformatics, biological sciences, statistics, or a related field, with 1+ years relevant work experience.
Additional Skills/Preferences
- Strong programming skills in Python and/or R including comfort with version control (Git), code review, testing, and writing maintainable code
- Demonstrated experience building data analysis pipelines, ideally using a workflow manager such as Nextflow, Snakemake, or WDL
- Working familiarity with bioinformatics file formats (VCF, BED, GTF, BAM, etc.) and standard tools (PLINK, samtools, bcftools, or similar)
- Familiarity with typical data types in high-throughput biology, including NGS data
- Hands-on experience or strong demonstrated interest in modern AI tooling — using LLMs through APIs, building MCP servers/connectors, prompt engineering, or wiring up agentic workflows
- Demonstrated ability to build stable and practical, reusable workflows and not just code for one-off analyses, with strong implementation skills in Python and modern AI/ML tooling
- A collaborative, low-ego mentality; you enjoy building tools that other people use and you take feedback well
- Comfort with cloud computing environments (AWS, GCP, or Azure) and Linux/command-line work
- Ability to work successfully in a matrixed environment
- Prior experience with statistical workflows/biomedical statistics
- Prior exposure to statistical genetics methods (GWAS, fine-mapping, MR, colocalization, burden testing) or large-scale genomic datasets (UK Biobank, gnomAD, GTEx, Open Targets)
- Prior experience with complex high-throughput biological data or experiments such as spatial transcriptomics, large-scale screens, or multi-omics studies
- Familiarity with R in addition to Python, particularly for statistical genetics packages
- Experience with relational and/or graph databases, and with biomedical ontologies
- Contributions to open-source projects or a public portfolio (GitHub, blog posts, demos)
- Prior experience in pharma, biotech, or academic genomics research
Resources Managed
This is an individual contributor role with no direct reports. The Applied Bioinformatics Engineer, Pipelines & AI will work closely with scientists, engineers, and external partners across Lilly Research Labs.
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 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 Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women’s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is
$166,500 - $266,200
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; and 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.
At Lilly, we unite caring with discovery to 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 Human Genomics and Translational Data Sciences team within Cardiometabolic Research Data Science is hiring a Bioinformatics Pipeline Engineer to help build, solidify, and scale the analytical pipelines our scientists rely on every day. Our work spans multiple omics workflows, including target discovery and target due diligence, single cell sequencing, genomics, proteomics and, increasingly, AI-assisted workflows that pull these analyses together into faster, more reproducible products for therapeutic area partners across Lilly Research Labs.
This role sits at the intersection of two worlds. On one side, we employ classical bioinformatics and statistical genetics pipelines — the kind of robust, reproducible, well-tested workflows that turn messy public and proprietary genomics data into trustworthy answers. On the other, the rapidly evolving stack of AI tooling — large language models like Claude, agentic workflows, building AI-friendly connectors like MCP (Model Context Protocol), and the code that lets scientists query complex datasets in natural language. We want someone who is genuinely curious about both, and keen to use both to improve the value we derive from our datasets to enable target support and novel target discovery.
You will not be expected to be a senior expert in either domain on day one. You will be expected to bring strong software engineering instincts, and a keen curiosity and creativity to enhance the value of the tools and datasets at our disposal. You will work closely with statistical geneticists, computational biologists, and other engineers — both within our team and across Lilly — to ship tools that make the science faster and more reliable.
Key Responsibilities
Pipeline Development and Engineering
- Support for computational biology workflows, including single cell, spatial, and other multi-omics analysis workflows for clinical and preclinical applications
- Use modern workflow managers (e.g. Nextflow, Snakemake, or similar) and containerization (Docker, Singularity) to make pipelines portable, testable, and reusable across projects and teams
- Help build and maintain reproducible analytical pipelines for statistical genetics and bioinformatics workflows
- Wrap and harden ad-hoc analytical scripts written by scientists into production-quality tools that can be re-run reliably by others
- Write tests, documentation, and clear examples so the pipelines you build are usable by colleagues with a range of technical backgrounds
AI-Enabled Tooling and Workflows
- Prototype agentic workflows that automate established and routine analytical tasks — for example, pulling target evidence across data sources, generating standardized due-diligence reports, or letting scientists interrogate complex datasets in natural language
- Build and maintain MCP connectors that expose internal data, public resources, and analytical pipelines to LLM-based agents and tools like Claude
- Identify and develop use cases where LLMs and agentic AI workflows can improve the speed, quality, consistency, or accessibility of work across therapeutic areas, focusing on end-to-end capabilities rather than isolated task completion
- Contribute to a shared library of reusable AI tooling, prompt patterns, and integration code that the team can build on. Define technical standards for evaluation, documentation, guardrails, and workflow quality so that AI-based solutions are trusted, reproducible, and suitable for repeated use across teams and projects
- Know the latest with the AI tooling landscape and bring back ideas the team can put to work. Help improve AI fluency among collaborators by demonstrating practical workflows
Collaboration Across Lilly Research Labs
- Partner closely with statistical geneticists, computational biologists, and software engineers within the Cardiometabolic Data Science group and across other Lilly Research Labs teams
- Work with therapeutic area partners to understand their analytical needs and translate them into pipeline requirements
- Coordinate with platform and engineering groups to ensure your pipelines integrate cleanly with broader Lilly infrastructure
- Contribute to internal knowledge sharing — code reviews, demos, documentation, and helping colleagues get unblocked
Basic Requirements
- B.S. in computer science, computational biology, bioinformatics, biological sciences, statistics, or a related field, with 10+ years relevant work experience,
- OR M.S. in computer science, computational biology, bioinformatics, biological sciences, statistics, or a related field, with 7+ years relevant work experience
- OR Ph.D. in computer science, computational biology, bioinformatics, biological sciences, statistics, or a related field, with 1+ years relevant work experience.
Additional Skills/Preferences
- Strong programming skills in Python and/or R including comfort with version control (Git), code review, testing, and writing maintainable code
- Demonstrated experience building data analysis pipelines, ideally using a workflow manager such as Nextflow, Snakemake, or WDL
- Working familiarity with bioinformatics file formats (VCF, BED, GTF, BAM, etc.) and standard tools (PLINK, samtools, bcftools, or similar)
- Familiarity with typical data types in high-throughput biology, including NGS data
- Hands-on experience or strong demonstrated interest in modern AI tooling — using LLMs through APIs, building MCP servers/connectors, prompt engineering, or wiring up agentic workflows
- Demonstrated ability to build stable and practical, reusable workflows and not just code for one-off analyses, with strong implementation skills in Python and modern AI/ML tooling
- A collaborative, low-ego mentality; you enjoy building tools that other people use and you take feedback well
- Comfort with cloud computing environments (AWS, GCP, or Azure) and Linux/command-line work
- Ability to work successfully in a matrixed environment
- Prior experience with statistical workflows/biomedical statistics
- Prior exposure to statistical genetics methods (GWAS, fine-mapping, MR, colocalization, burden testing) or large-scale genomic datasets (UK Biobank, gnomAD, GTEx, Open Targets)
- Prior experience with complex high-throughput biological data or experiments such as spatial transcriptomics, large-scale screens, or multi-omics studies
- Familiarity with R in addition to Python, particularly for statistical genetics packages
- Experience with relational and/or graph databases, and with biomedical ontologies
- Contributions to open-source projects or a public portfolio (GitHub, blog posts, demos)
- Prior experience in pharma, biotech, or academic genomics research
Resources Managed
This is an individual contributor role with no direct reports. The Applied Bioinformatics Engineer, Pipelines & AI will work closely with scientists, engineers, and external partners across Lilly Research Labs.
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 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 Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women’s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is
$166,500 - $266,200
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; and 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.
See all 81+ H-1B Visa Bioinformatics Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Bioinformatics Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship in Bioinformatics
Map your degree to the role
USCIS requires your degree field to directly relate to bioinformatics work. A degree in computer science or biology alone can trigger an RFE, document how your coursework covers both computational and biological domains before applying.
Target employers with LCA filing history
Search OFLC disclosure data filtered to bioinformatics-related SOC codes to see which pharma, genomics, and research employers have filed LCAs. Migrate Mate surfaces this data so you can prioritize companies with active sponsorship records.
Check prevailing wage before negotiating
Your offered salary must meet the DOL prevailing wage for your job zone and location. Run the OFLC Wage Search using your specific SOC code before any offer discussion so you can negotiate within a range USCIS won't flag.
Verify your employer's E-Verify enrollment early
If you're on OPT and transitioning to H-1B, your STEM OPT employer must be E-Verify enrolled. Confirm enrollment status before accepting a bioinformatics role, switching employers mid-extension restarts the compliance clock.
Use O*NET to frame your specialty occupation case
Bioinformatics spans multiple SOC codes and adjudicators sometimes challenge specialty occupation status. Pull the O*NET occupation profile for your specific role title and use its education and training data to anchor your employer's support letter.
File premium processing if your start date is rigid
Bioinformatics grant cycles and clinical trial timelines often mean rigid start dates. USCIS premium processing guarantees a 15-business-day adjudication decision, reducing the risk that delayed approval disrupts a project-tied onboarding date.
H-1B Visa Bioinformatics: Frequently Asked Questions
Does bioinformatics qualify as a specialty occupation for H-1B purposes?
Yes, bioinformatics qualifies as a specialty occupation because the work requires at minimum a bachelor's degree in a directly related field such as computational biology, bioinformatics, or computer science with a biological sciences minor. USCIS expects the employer to document why a specialized degree, not just any bachelor's, is required for the specific role.
Which SOC code applies to bioinformatics jobs for LCA filing?
Most bioinformatics positions are filed under SOC 19-1029 (Biological Scientists, All Other) or 15-2099 (Mathematical Science Occupations, All Other), depending on whether the role is research-focused or computationally weighted. The employer chooses the code, but it directly determines your prevailing wage tier, so confirm it matches your actual job duties before the LCA is submitted to DOL.
How do I find employers who actively sponsor H-1B visas for bioinformatics roles?
Migrate Mate filters job listings by employers with verified H-1B LCA filing history, including companies in pharma, genomics, and academic medical research. Searching by role type and location shows you which organizations have a track record of sponsoring bioinformatics professionals, rather than guessing based on company size or industry.
Can a bioinformatics employer file my H-1B if I'm still finishing my degree?
Yes, if you'll complete your degree before the H-1B start date of October 1, your employer can submit the registration in March for a cap-subject H-1B. USCIS allows filing before graduation as long as the degree is conferred by the time the petition is approved or the employment begins, whichever is later.
What happens to my H-1B status if my bioinformatics role shifts from research to software development?
A material change in job duties requires your employer to file an amended H-1B petition before the change takes effect. If the new role falls under a different SOC code or prevailing wage level, the employer must also file a new LCA with DOL. Failing to amend can put your status out of compliance, so flag any significant duty changes to your employer's immigration counsel promptly.