Genomic Scientist- Pipeline Development

Boston Children’s Hospital; Boston (MA); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Boston Children’s Hospital in Boston, MA seeks a Genomic Data Scientist to design scalable bioinformatics pipelines and automate multi-omics analyses for pediatric research.

You will work with PhD-level bioinformaticians to implement Nextflow/Snakemake workflows and contribute to clinical-genomics projects using Docker/Singularity, Git, and HPC resources.

Qualifications

• Bachelor's degree (or higher) in a quantitative field; PhD preferred.
• 1+ year of experience building automated bioinformatics pipelines.
• Experience with Nextflow, WDL, or Snakemake.
• Proficient in Python, R, and Bash in Linux HPC environments.
• Experience with Docker/Singularity and Git.
• Experience analyzing multi-omics data (WGS/WES, RNA, methylation).
• Familiarity with clinical NGS frameworks or ACMG guidelines in a research setting.

Responsibilities

• Design, build, and maintain scalable, reproducible bioinformatics pipelines for multi-omics data.
• Execute exploratory and inferential analyses using advanced statistics and ML techniques.
• Containerize tools and optimize code for HPC clusters; manage version control.
• Collaborate with physician-scientists to translate data into insights and milestones.
• Document pipelines and contribute to publications and internal forums.

Skills

Python

R

Bash

Nextflow

WDL

Snakemake

Git

Linux/Unix

HPC

Machine Learning

Statistics

Education

Bachelor's degree

PhD preferred

Tools

Docker

Singularity

Nextflow

Snakemake

WDL

Git

Job description

Position Summary
Research Informatics supports basic, translational, and clinical pediatric research by delivering cutting-edge digital tools, high-performance computing (HPC), and advanced data science expertise. We bring together PhD-level bioinformaticians, genomic scientists, software engineers, and HPC specialists to collaborate with physician-scientists on work ranging from CryoEM to translational genomics.
As a Genomic Data Scientist, you will drive pipeline engineering and high-dimensional multi-omics analysis across pediatric rare disease initiatives. Working under general scientific direction, you will serve as a key technical and analytical contributor to genomics projects, architecting automated, reproducible workflow systems (e.g., Nextflow, WDL, Snakemake) to process and interpret RNA-seq, methylation, long-read, and whole genome/exome (WGS/WES) data.
Key Responsibilities

• Pipeline Engineering & Workflow Automation: Design, build, optimize, and maintain scalable, reproducible bioinformatics pipelines and automated variant interpretation workflows for research and clinical-grade multi-omics data.
• Hypothesis-Driven Data Analysis: Deploy automated analytical workflows to execute rigorous exploratory and inferential data processing on high-dimensional genomic datasets using advanced statistics, machine learning, and quantitative modeling.
• HPC & Infrastructure Optimization: Containerize computational tools (Docker/Singularity), implement version control (Git), and optimize code performance for efficient execution across High-Performance Computing (HPC) clusters.
• Biological Discovery & Project Execution: Partner with physician-scientists to translate raw multi-omics data into biological insights, managing computational project milestones and troubleshooting pipeline bottlenecks with minimal supervision.
• Documentation & Scientific Communication: Thoroughly document computational pipelines and code bases, contribute to peer-reviewed scientific publications, and present analytical methods at internal and external research forums.

Minimum Qualifications
Education:

• Bachelor's degree; PhD in Genetics, Genomics, Computational Biology, Bioinformatics, or a related quantitative field highly preferred.

Experience:

• A minimum of one year of position-specific experience might potentially include experience acquired through MSc or Ph.D. studies.
• Demonstrated experience building, maintaining, and automating bioinformatics pipelines using workflow orchestration engines (e.g., Nextflow, WDL, Snakemake).
• Strong programming proficiency in Python, R, and Bash in Linux/Unix High-Performance Computing (HPC) environments, including experience with containerization (Docker/Singularity) and version control (Git).
• Computational experience analyzing multi-omic datasets (WGS/WES, RNA sequencing, methylation, or long-read platforms).
• Experience with human genetics research, variant annotation tools, and familiarity with clinical NGS testing frameworks or ACMG interpretation guidelines in a research setting.
• Demonstrated ability to manage pipeline development tasks independently under general guidance, troubleshoot technical software issues, and collaborate effectively with multidisciplinary research teams.