ZipRecruiter

Log In

1

Senior Genomic Data Analyst Jobs (NOW HIRING)

Legend Biotech USA, Inc.

Legend Biotech is seeking a Scientist/Sr. Scientist, Bioinformatics Data as part of the Early Drug ... Key Responsibilities Analyze diverse and large-scale genomic datasets (e.g., RNA-seq, scRNA-seq ...

MSD Malaysia

Associate Director, Data Science

Boston, MA · On-site

$160 - $251/hr

Analyze, summarize, and visualize the findings from large multi-modal clinico-genomic datasets ... Experience with analysis of genomic data originating from clinical trials. * Understanding of the ...

previous pagenext page

Showing results 21-40

All JobsTechnology JobsData JobsBioinformatics Scientist JobsSenior Genomic Data Analyst Jobs

Senior Genomic Data Analyst information

See salary details

$55K

$99.2K

$135.5K

How much do senior genomic data analyst jobs pay per year?

As of Sep 2, 2026, the average yearly pay for senior genomic data analyst in the United States is $99,231.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,000.00 and $108,500.00 per year, depending on experience, location, and employer.

What is a senior genomic data analyst?

A Senior Genomic Data Analyst is a professional who specializes in analyzing and interpreting large-scale genomic data sets, often using advanced computational and statistical methods. They play a key role in biomedical research, healthcare, and biotechnology by identifying genetic patterns, variants, and potential disease associations. In this senior role, they may also guide research strategies, develop analytic pipelines, and collaborate with interdisciplinary teams to drive scientific discoveries. Their expertise helps advance our understanding of genetics and supports the development of personalized medicine.

How does a senior genomic data analyst typically collaborate with cross-functional teams in a research or clinical setting?

Senior Genomic Data Analysts frequently work alongside bioinformaticians, laboratory scientists, clinicians, and IT specialists to interpret and manage complex genomic datasets. Collaboration often involves leading discussions to define project goals, ensuring data quality, and translating analytical results into actionable insights for research or patient care. Effective communication and the ability to present complex findings in a clear manner are critical, as these analysts bridge the gap between raw data and practical applications. Regular meetings, joint problem-solving sessions, and shared project management tools are common ways this collaboration is structured.

What are the key skills and qualifications needed to thrive as a senior genomic data analyst, and why are they important?

A Senior Genomic Data Analyst requires advanced expertise in bioinformatics, genomics, and statistical analysis, typically supported by a master's or PhD in a relevant field. Proficiency with tools such as Python, R, next-generation sequencing (NGS) data analysis platforms, and experience with databases like Ensembl or UCSC Genome Browser is essential. Strong problem-solving, communication, and collaborative skills help translate complex genomic findings into actionable insights for research or clinical teams. These competencies are crucial for ensuring accurate data interpretation, effective collaboration, and meaningful contributions to advances in genomics.

What is the difference between Senior Genomic Data Analyst vs Genomic Data Analyst?

AspectSenior Genomic Data AnalystGenomic Data Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Genetics, or related field; experience in data analysisBachelor's degree in related field; entry-level experience preferred
Work EnvironmentResearch labs, biotech companies, healthcare institutionsResearch projects, data management, laboratory settings
Employer & Industry UsagePharmaceuticals, biotech, academic researchGenomics labs, research institutions, healthcare providers
Common Search & ComparisonOften compared for experience level and responsibilitiesEntry-level counterpart, less responsibility

The main difference between a Senior Genomic Data Analyst and a Genomic Data Analyst lies in experience, responsibilities, and expertise. Senior analysts typically have more advanced skills, oversee complex projects, and provide mentorship, whereas Genomic Data Analysts are often entry-level or early-career professionals focusing on data processing and analysis tasks.

More about Senior Genomic Data Analyst jobs

What cities are hiring for Senior Genomic Data Analyst jobs?

Cities with the most Senior Genomic Data Analyst job openings:

What are the most commonly searched types of Genomic Data Analyst jobs?

The most popular types of Genomic Data Analyst jobs are:

What states have the most Senior Genomic Data Analyst jobs?

States with the most job openings for Senior Genomic Data Analyst jobs include:

What job categories do people searching Senior Genomic Data Analyst jobs look for?

The top searched job categories for Senior Genomic Data Analyst jobs are:

Senior Genomic Data Analyst jobs near you
Infographic showing various Senior Genomic Data Analyst job openings in the United States as of August 2026, with employment types broken down into 61% Full Time, 13% Part Time, 13% Temporary, and 13% Contract. Highlights an 74% In-person, 13% Hybrid, and 13% Remote job distribution, with an average salary of $99,231 per year, or $47.7 per hour.

Associate Bioinformatics Data Scientist

Signature Science, LLC

Charlottesville, VA

$56K - $57K/yr

Full-time

Re-posted 4 days ago

Job description

Position Purpose:   

A bioinformatics data scientist is responsible for providing experimental design consulting and data analysis for large, high-throughput genomic experiments, with a focus on forensics and metagenomics. The bioinformatics data scientist will be responsible for designing and implementing annotated code for managing, manipulating, and analyzing large-scale genomic data, and for preparing thorough documentation and reporting.

This position is a full-time, on-site role at the Signature Science office in Charlottesville, VA.

Essential Duties and Responsibilities:

  • Develop tools for management, analysis and interpretation of high-density microarray and whole genome sequencing data.
  • Manage, manipulate, and analyze data using a combination of R, python, and UNIX tools.
  • Use established domain-specific open-source software and tools to manipulate and analyze genomic data.
  • Implement and execute data processing workflows and automated analytic pipelines.
  • ·     Apply literateprogramming methods to develop reproducible workflows that produce consistent, standardized tables and figures.
  • Conduct workflow benchmarking and documentation, identifying inconsistencies and resolving data problems.
  • Prepare SOPs, document source code/workflows, and write reports to summarize computational requirements, processing status, and customized analysis results.

Required Knowledge, Skills & Abilities:

  • Advanced proficiency working in a Unix/Linux environment.
  • Advanced proficiency with open-source software, tools, and databases for analyzing next-generation sequencing data (whole-genome sequencing, RNA-seq, epigenetics, microbiome, and metagenomics).
  • Proficiency working with and developing using Docker and/or Singularity container technology.
  • Proficiency using version Control software (e.g., Git or similar) to manage programming code.
  • Proficiency with Python, Perl, or another scripting language.
  • Proficiency with R, RMarkdown, and the "tidyverse" tools for data analysis.
  • Preferred: Experience with NextFlow, SnakeMake, or similar workflow/pipeline management systems.
  • Preferred: Familiarity with developing and querying relational databases.
  • Preferred: Familiarity with AWS and/or Azure cloud computing.

Education/Experience:

  • BA or BS in Computer Science, Bioinformatics, or related field
  • Experience managing and analyzing large-scale datasets produced sequencing platforms and delivering solutions for managing, visualizing, analyzing, and interpreting genomic data
  • Experience using Linux/Unix text processing tools, R, and other open-source tooling to manipulate and format data, to assess data quality, and analyze data.

Clearance:

  • This position requires that the candidate be willing and able to complete a successful background screening for a security clearance. Candidates with a current security clearance will receive preference.

Supervisory Responsibilities:

  • May serve as a bioinformatics task lead.

Working Conditions/ Equipment:

  • Ability to work in varying conditions to include: traditional office environments with sedentary extended periods required for code development and testing.
Employment Type: FULL_TIME

Apply