Statistical Genetics Platform Engineer
Eli Lilly and Company
full-time
Posted on:
Location Type: Office
Location: Boston • Massachusetts • 🇺🇸 United States
Visit company websiteSalary
💰 $166,500 - $266,200 per year
Job Level
Mid-LevelSenior
Tech Stack
AWSAzureCloudGoogle Cloud PlatformPython
About the role
- Design and implement robust, scalable computational pipelines for statistical genetics analyses, including workflows for GWAS, polygenic risk scores, fine-mapping, colocalization and variant annotation
- Develop and maintain platform tools and APIs that enable researchers to efficiently process genomic data at scale (biobanks, population cohorts, multi-omics datasets)
- Build infrastructure for reproducible research, including containerization, workflow orchestration, and version control for analytical pipelines
- Optimize computational performance of statistical genetics algorithms and implement distributed computing solutions for large-scale analyses
- Collaborate with statistical geneticists and computational biologists to translate methodological innovations into production-ready software
- Establish best practices for data access, quality control, validation, and documentation across genomic analysis pipelines
- Maintain and improve existing codebases, ensuring code quality, testing coverage, and comprehensive documentation
- Monitor platform performance, solve issues, and implement improvements based on user feedback and evolving research needs
- Support the integration of AI-based tools and required MLOps infrastructure
Requirements
- Master’s in Computer Science, Statistical Genetics, Bioinformatics or related field and 6+ years post-Master’s experience (in industry or large-scale non-academic institutions, e.g. Broad, NIH), OR PhD in Computer Science, Statistical Genetics, Bioinformatics or related field and 3+ years post-PhD experience (in industry or large-scale non-academic institutions, e.g. Broad, NIH)
- Strong programming skills in languages commonly used in genomics research (Python, R)
- Demonstrable understanding of statistical genetics concepts including GWAS, heritability estimation, genetic correlation, rare variant analysis, and population structure
- Experience using standard tools and formats for genetic data (VCF, BGEN, PLINK, BAM/CRAM) and genomic databases
- Proficiency with workflow management systems (Nextflow, Cromwell/WDL) and containerization technologies
- Experience with high-performance computing environments, cloud platforms (AWS, GCP, Azure), or distributed computing frameworks
- Strong problem-solving abilities and attention to detail in handling complex biological datasets
- Ability to prioritize and manage multiple competing priorities within a fast-paced environment
Benefits
- 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)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonRGWASpolygenic risk scoresfine-mappingcolocalizationvariant annotationstatistical geneticshigh-performance computingMLOps
Soft skills
problem-solvingattention to detailprioritizationtime management
Certifications
Master’s in Computer ScienceMaster’s in Statistical GeneticsMaster’s in BioinformaticsPhD in Computer SciencePhD in Statistical GeneticsPhD in Bioinformatics