Scientist I, Computational Biology - Contract

Editas Medicine; Cambridge (MA); Presencial; USD 110.000 - 160.000; Jornada completa

Descripción de la vacante

Editas Medicine in Cambridge, MA is seeking a Scientist I / Senior Associate Scientist to support the development of NGS data analysis pipelines for CRISPR genome-editing programs. You will analyze diverse sequencing data and optimize workflows to advance research and clinical programs.

The role requires hands-on data analysis, cross-functional collaboration, and strong documentation. PhD with 0+ years of experience or equivalent seniority is expected.

Formación

• PhD in bioinformatics, computer science, biology or a related computational discipline.
• Experience with NGS data analysis and various sequencing workflows.

Responsabilidades

• Perform sophisticated computational analyses of NGS data and develop data visualizations.
• Collaborate with computational biology, informatics, and analytical development teams to maintain robust pipelines.
• Define, troubleshoot, and optimize analysis specifications for novel NGS analyses.
• Maintain well-documented workflows and study reports for research and regulatory activities.
• Present scientific findings to leadership to inform therapeutic programs.

Conocimientos

NGS data analysis

Python

R

Linux/Unix

Git

AWS cloud

Docker

Snakemake

AI tools (Claude Code)

Educación

PhD in bioinformatics / computational biology / related field

Bachelor's degree + 6+ years OR Master's + 4+ years

Herramientas

Docker

Snakemake

AWS

Git

Descripción del empleo

At Editas Medicine, we are pioneering the possible. Our mission and commitment is to translate the power and potential of the CRISPR/Cas12a and CRISPR/Cas9 genome editing systems into a robust pipeline of medicines for people living with serious diseases around the world. Our goal is to discover, develop, manufacture, and commercialize transformative, durable, precision genomic medicines for a broad class of diseases.

Why Choose Editas?

At Editas Medicine, we're a team of passionate problem solvers, harnessing the power and potential of CRISPR gene editing to transform the future of medicine. Driven by a shared purpose to serve people living with serious diseases, we succeed together through collaboration, mutual respect, and innovation. If you want to be part of a team where your voice is heard and respected, where you can operate at the forefront of gene editing, and push the boundaries of what's possible in medicine, come join us and become an Editor!

Decoding the Role

The Genomics and Bioinformatics team at Editas Medicine is seeking a motivated and highly collaborative Scientist I/Senior Associate Scientist to support the development of analysis pipelines applied to Next Generation Sequencing (NGS) data for CRISPR gene-editing programs. This is a role with opportunities to contribute to the development, optimization, and execution of NGS data analysis pipelines supporting research, preclinical-stage, and clinical-stage programs. The successful candidate will apply their experience with NGS data analysis, sequencing platforms, assay quality control, and data interpretation to generate high-quality analyses and advance new analytical capabilities. The candidate will execute and optimize existing NGS data analysis workflows while contributing to the development and implementation of new analysis methods. Areas of work may include analysis of data from targeted amplicon sequencing, off-target verification, long-read sequencing, and RNA sequencing. The ideal candidate combines strong hands‑on data analysis skills with an understanding of NGS workflows and a demonstrated ability to troubleshoot complex assays. The individual will work closely with scientists across Research, Translational Sciences, Process Development, and other functions. The candidate will be expected to communicate results clearly, maintain superior documentation, and contribute scientifically to project strategy and assay development.

In this role you will:

• Perform sophisticated computational analyses of NGS data through deep critical thinking, incorporation of published findings and best practices in the field, and intuitive data science visualizations.
• Partner with computational biology, informatics, and analytical development teams to develop and maintain reproducible, usable, version‑controlled, and robust computational biology pipelines and workflows.
• Define, troubleshoot, and optimize analysis specifications from novel NGS analyses to define assay acceptance criteria.
• Maintain well‑documented workflows, author study reports, and provide technical documentation to support research, analytical development, and regulatory activities.
• Present scientific findings to a broad range of audiences, including senior leadership, to help inform decision‑making for therapeutic programs.

The Ideal Transcript Scientist I level will have a PhD in bioinformatics, computer science, biology, or a relevant computational discipline. Senior Associate Scientist will have a Bachelor's degree with 6+ years of experience or Master's degree and 4+ years in these areas. Demonstrated hands‑on experience with NGS data analysis (e.g. targeted amplicon sequencing, whole genome sequencing, RNA sequencing). Experience with guide RNA sequencing is a plus. Demonstrated programming and developer skills (e.g. Linux/Unix, Python, R, git), with experience in cloud computing (e.g. AWS), docker, Snakemake, and agentic AI tools such as Claude Code. Familiarity with bioinformatics packages and algorithms related to NGS data analysis (e.g. bowtie2, star, minimap2, samtools, Bioconductor, etc.). Strong documentation and organizational skills, including experience with electronic laboratory notebooks such as Benchling. Ability to work effectively in a collaborative, multidisciplinary, and timeline‑driven environment. Excellent written and verbal communication skills.

Preferred Qualifications

• Experience analyzing NGS data from CRISPR or other gene‑editing modalities, including characterization of on‑target editing, off‑target editing, structural variants, or other editing outcomes.
• Experience with analysis of data from Oxford Nanopore sequencing is highly desirable.
• Experience with analysis of guide RNA sequencing data from Illumina or Oxford Nanopore sequencing platforms.
• Experience with analysis of data from high‑throughput targeted sequencing and multiplexed amplicon assays.
• Experience supporting assay development in a biotechnology or pharmaceutical environment.
• This role is