Computational Genomics Research Scientist

Vertex Pharmaceuticals Incorporated; Boston (MA); Hybrid; USD 112,000 - 168,000; Full time

Benefits offered by this job

Medical, dental, vision benefits

Generous paid time off

Commuting subsidy

401(k) and matching

Student loan repayment support

Job summary

Vertex Pharmaceuticals Incorporated is seeking a Computational Genomics Research Scientist to advance cell and gene therapy programs in Boston. The role integrates diverse genomic datasets, develops analytical workflows, and produces biological insights to drive early research across disease programs.

The position is Boston-based, hybrid (3 days onsite) and lives within Vertex's global Data and Computational Sciences organization, collaborating with stem cell biology, immunology, gene editing,

Qualifications

• Proven track record in genomic data analysis and interpretation.
• Experience with single-cell genomics and spatial transcriptomics experiments.
• Proficiency in Python and/or R for scientific computing.

Responsibilities

• Collaborate with cross-functional teams to address genomic questions.
• Advance spatial transcriptomics methods and share best practices.
• Integrate bulk RNA-seq, single-cell, and spatial data to generate insights.
• Perform rigorous computational analyses with strong statistics and visualization.
• Distill findings into actionable recommendations for research teams.
• Document workflows and ensure reproducibility and traceability.

Skills

Genomic data analysis

Single-cell & spatial transcriptomics

Bioinformatics tools

Statistics

Education

Ph.D. in computational biology / related field

M.S. in related field with 3+ years industry experience

Tools

Python

R

Linux HPC / Cloud

Job description

Job Description

We are seeking a Computational Genomics Research Scientist to support the development of transformative cell and gene therapies across Vertex's research portfolio. This Boston-based position is part of the global Data and Computational Sciences organization and will collaborate closely with research teams spanning stem cell biology, immunology, gene editing, and pre-clinical development to design studies, execute and analyze complex genomic analyses, and ultimately generate biological insights that drive early research across multiple disease programs. As an embedded computational scientist, you will be responsible for performing bulk and single-cell sequencing analyses, spatial transcriptomics, and multiomic profiling to help uncover the molecular programs that govern therapeutic cell identity, differentiation, function, and safety to accelerate the development of next-generation cell and gene therapies.

This is a Boston based, hybrid position requiring 3 days/week onsite.

Key Responsibilities

• Collaborate closely with cross-functional research teams to identify key scientific questions that can be addressed through genomics, sequencing, and bioinformatics approaches.
• Lead the application and advancement of spatial transcriptomics methods, collaborating across teams and sites to develop, implement, and share analytical best practices.
• Analyze and integrate diverse genomic datasets, including bulk RNA-seq, single-cell profiling, spatial transcriptomics, and other multiomic datasets to generate actionable insights.
• Perform sophisticated computational analyses of sequencing and other biological data through deep critical thinking, incorporation of published findings and best practices from the field, strong statistical rigor, and data science visualizations
• Distill complex analyses and scientific results into key take-home messages and recommendations for next steps to a broad audience.
• Partner with computational and software teams to improve analytical workflows, reproducibility, usability, and robustness.
• Practice reproducible research and maintain well-documented, version-controlled analytical workflows.
• Author study reports and technical documentation to support research and regulatory activities.
• Evaluate emerging genomics technologies and computational methods and incorporate new approaches where appropriate.

Knowledge and Skills:

• A proven track record in the analysis, visualization, and interpretation of genomic and next-generation sequencing (NGS) data
• Solid scientific understanding of gene editing, the role of genetic variation in human disease, molecular biology, and cellular biology
• Expertise with applying computational methods and bioinformatics tools to large-scale data
• Solid understanding of statistics

Education and Experience:

• Ph.D. in computational biology, bioinformatics, genomics, systems biology, biomedical engineering, statistics, computer science, or a related quantitative discipline, with 0-3 years of relevant postdoctoral or industry experience; or a Master's degree in a related field with 3+ years of relevant industry experience.
• Demonstrated expertise in the design, analysis, visualization, and interpretation of single-cell genomics and spatial transcriptomics experiments
• Proficiency in Python and/or R for scientific computing and data analysis.
• Experience working in Linux-based high-performance computing (HPC) and/or cloud computing environments.
• Strong foundation in statistics, experimental design, and reproducible computational research.
• Proven ability to derive biological insight from complex datasets and translate findings into actionable recommendations for research teams.
• Excellent communication and presentation skills, with the ability to effectively convey complex scientific findings to multidisciplinary audiences.
• Demonstrated ability to work collaboratively within cross-functional teams and contribute to a positive, team-oriented environment.

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Pay Range:

$112,000 - $168,000

Disclosure Statement:

The range provided is based on what we believe is a reasonable estimate for the base salary pay range for this job at the time of posting. This role is eligible for an annual bonus and annual equity awards. Some roles may also be eligible for overtime pay, in accordance with federal and state requirements. Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.

At Vertex, our Total Rewards offerings also include inclusive market-leading benefits to meet our employees wherever they are in their career, financial, family and wellbeing journey while providing flexibility and resources to support their growth and aspirations. From medical, dental and vision benefits to generous paid time off (including a week-long company shutdown in the Summer and the Winter), educational assistance programs including student loan repayment, a generous commuting subsidy, matching charitable donations, 401(k) and so much more.

Flex Designation:

Hybrid-Eligible Or On-Site Eligible

Flex Eligibility Status:

In this Hybrid-Eligible role, you can choose to be designated as:
1. Hybrid: work remotely up to two days per week; or select
2. On-Site: work five days per week on-site with ad hoc flexibility.

Note: The Flex status for this position is subject to Vertex's Policy on Flex @ Vertex Program and may be changed at any time.

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Company Information

Vertex is a global biotechnology company that invests in scientific innovation.

Vertex is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, sexual orientation, marital status, or any characteristic protected under applicable law. Vertex is an E-Verify Employer in the United States. Vertex will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should make a request to the recruiter or hiring manager, or contact Talent Acquisition at [e-mail]