ZipRecruiter

Log In

2

Entry Level Genomics Data Scientist Jobs (NOW HIRING)

GRAIL

Senior Data Scientist # 4630

Menlo Park, CA · On-site

$187K/yr

In this role, you will work at the intersection of machine learning, genomics, and clinical science ... Strong expertise in data analysis using Python or R * Deep understanding of modern machine learning ...

GRAIL

Senior Data Scientist # 4630

Menlo Park, CA

$187K/yr

In this role, you will work at the intersection of machine learning, genomics, and clinical science ... Strong expertise in data analysis using Python or R * Deep understanding of modern machine learning ...

GRAIL

Senior Data Scientist # 4630

Menlo Park, CA · On-site

$187K/yr

In this role, you will work at the intersection of machine learning, genomics, and clinical science ... Strong expertise in data analysis using Python or R * Deep understanding of modern machine learning ...

Novartis

Human Genetics Data Scientist

Cambridge, MA · On-site

$114K - $211K/yr

Summary We are seeking a human genetics data scientist to join the Human Genetics & Targets group ... Experience processing and analyzing biobank-scale genomic data (e.g. UK Biobank, All of Us, FinnGen ...

next page

Showing results 1-20

All JobsGenomics Data Scientist JobsEntry Level Genomics Data Scientist Jobs

Entry Level Genomics Data Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do entry level genomics data scientist jobs pay per year?

As of Jul 14, 2026, the average yearly pay for entry level genomics data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

How to become a genomic data scientist?

To become a genomic data scientist, one typically needs a bachelor's degree in bioinformatics, genetics, computer science, or a related field, followed by gaining skills in programming languages like Python or R, and experience with genomic data analysis tools. Advanced roles often require a master's or Ph.D. in a relevant discipline and familiarity with high-throughput sequencing technologies and statistical methods. Building a strong foundation in biology, data analysis, and computational skills is essential for success in this field.

What is the difference between Entry Level Genomics Data Scientist vs Entry Level Bioinformatics Analyst?

AspectEntry Level Genomics Data ScientistEntry Level Bioinformatics Analyst
Required CredentialsBachelor's in Bioinformatics, Genetics, or related field; some roles prefer internshipsBachelor's in Bioinformatics, Biology, or related field; similar certifications
Work EnvironmentResearch labs, biotech companies, healthcare institutionsResearch institutions, biotech firms, academic settings
Industry UsageGenomics research, personalized medicine, biotech developmentGenomics, molecular biology, clinical research
Common Search/ComparisonYesYes

Both roles require similar educational backgrounds and work in genomics-related environments. The main difference is that a Genomics Data Scientist focuses more on analyzing large genomic datasets and developing models, while a Bioinformatics Analyst often performs data processing and interpretation tasks. Understanding these distinctions helps job seekers identify the best fit for their skills and career goals.

Is 40 too late for data science?

Entry level genomics data scientists can start at age 40, as the field values relevant skills such as programming, statistical analysis, and knowledge of genomics tools. Many professionals successfully transition into data science later in their careers by gaining certifications and practical experience, making age less of a barrier than skill set and dedication.

Can I get a data scientist job with no experience?

Entry-level genomics data scientist positions typically require some foundational knowledge in biology, programming, and data analysis, but they often do not require extensive professional experience. Candidates can improve their chances by gaining skills in tools like Python, R, and bioinformatics software, and obtaining relevant certifications or completing internships. Demonstrating a strong understanding of genomics concepts and analytical skills can help entry-level applicants secure such roles.

How do I become a data scientist with no experience?

To become an entry-level genomics data scientist with no experience, focus on building foundational skills in programming (such as Python or R), statistics, and biology through online courses or tutorials. Gaining practical experience with datasets, learning relevant tools like Jupyter notebooks, and obtaining certifications can improve your prospects; internships or volunteer projects also provide valuable hands-on experience.
More about Entry Level Genomics Data Scientist jobs
What cities are hiring for Entry Level Genomics Data Scientist jobs? Cities with the most Entry Level Genomics Data Scientist job openings:
What are the most commonly searched types of Genomics Data Scientist jobs? The most popular types of Genomics Data Scientist jobs are:
What states have the most Entry Level Genomics Data Scientist jobs? States with the most job openings for Entry Level Genomics Data Scientist jobs include:
What job categories do people searching Entry Level Genomics Data Scientist jobs look for? The top searched job categories for Entry Level Genomics Data Scientist jobs are:
Entry Level Genomics Data Scientist jobs near you
Infographic showing various Entry Level Genomics Data Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Associate Bioinformatics Data Scientist

Associate Bioinformatics Data Scientist

Signature Science, LLC

Charlottesville, VA

$75K/yr

Full-time

Posted 13 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 literate‑programming 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.