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Associate Bioinformatician Jobs (NOW HIRING)

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Design, develop, and maintain bioinformatics pipelines for the analysis of next-generation ... Participate in cross-disciplinary mentoring and training of associate scientists. * Promote data ...

$17.10 - $29.09/hr

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Run computational bioinformatics pipelines on a local high-performance computing cluster to analyze genomic datasets. * Conduct variant analysis and curation, helping to identify genomic variants ...

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Associate Bioinformatician information

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$54.5K

$96.2K

$139K

How much do associate bioinformatician jobs pay per year?

As of Aug 15, 2026, the average yearly pay for associate bioinformatician in the United States is $96,169.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,000.00 and $109,500.00 per year, depending on experience, location, and employer.

What is the difference between Associate Bioinformatician vs Bioinformatics Analyst?

AspectAssociate BioinformaticianBioinformatics Analyst
Required CredentialsBachelor's or Master's in Bioinformatics, Biology, or related fieldBachelor's or Master's in Bioinformatics, Computer Science, or related field
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch institutions, healthcare, biotech firms
Employer & Industry UsagePharmaceuticals, biotech, academiaHealthcare, research, biotech
Common Search & ComparisonYesYes

The Associate Bioinformatician typically supports data analysis and computational tasks under supervision, focusing on research projects. The Bioinformatics Analyst often performs data interpretation, reporting, and may have more client-facing or project management responsibilities. Both roles require similar educational backgrounds but differ slightly in scope and responsibilities within the bioinformatics field.

What are the key skills and qualifications needed to thrive as an associate bioinformatician, and why are they important?

To thrive as an Associate Bioinformatician, you need a solid background in biology, statistics, and computer science, often supported by a degree in bioinformatics or a related field. Familiarity with programming languages such as Python or R, experience with bioinformatics tools (e.g., BLAST, Bowtie), and knowledge of databases like GenBank are typically required. Strong problem-solving skills, attention to detail, and the ability to communicate complex data clearly make someone stand out in this position. These skills ensure accurate data analysis, effective collaboration with research teams, and meaningful contributions to scientific discoveries.

What are some common challenges faced by an associate bioinformatician when working on interdisciplinary teams?

As an Associate Bioinformatician, one common challenge is effectively communicating complex computational findings to colleagues from diverse backgrounds, such as biologists or clinicians, who may not have extensive coding or data analysis experience. Balancing the need to deliver accurate, reproducible results with project deadlines can also be demanding, especially when handling large datasets or troubleshooting data quality issues. Additionally, adapting to rapidly evolving bioinformatics tools and staying updated on best practices is essential for success in collaborative research environments.

What does an associate bioinformatician do?

An Associate Bioinformatician is a professional who applies computational and statistical techniques to analyze biological data, such as DNA, RNA, or protein sequences. They often work closely with scientists and researchers to interpret large datasets generated from experiments, helping to uncover insights in genomics, transcriptomics, and other 'omics' fields. Their responsibilities may include developing and running bioinformatics pipelines, managing databases, and preparing data visualizations or reports for research projects. Typically, this is an entry- to mid-level role, ideal for those with a strong background in biology, computer science, or related fields.
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What cities are hiring for Associate Bioinformatician jobs?

Cities with the most Associate Bioinformatician job openings:

What are the most commonly searched types of Bioinformatician jobs?

The most popular types of Bioinformatician jobs are:

What states have the most Associate Bioinformatician jobs?

States with the most job openings for Associate Bioinformatician jobs include:

Infographic showing various Associate Bioinformatician job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 28% Part Time, 1% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $96,169 per year, or $46.2 per hour.

Associate Director of Bioinformatics (Women's Health and Organ Health)

Natera

OR • On-site, Remote

Full-time

Posted 4 days ago


Natera rating

7.7

Company rating: 7.7 out of 10

Based on 38 frontline employees who took The Breakroom Quiz

56th of 120 rated laboratories


Job description

Natera is seeking an Associate Director to lead a team of Bioinformatics Scientists in our Women's Health and Organ Health research organization. You will oversee the scientific planning and execution of research and assay-development of diagnostic projects, and you will be responsible for creating production-ready pipeline components. You will manage your team and its professional growth, the research strategy behind new product development, and the handoff of research work into production. 

The role calls for deep experience in algorithm and assay development, NGS data processing across multiple modalities, and the full life cycle of diagnostic product research and development in a regulated (CLIA) setting. You will evaluate new technologies and NGS assays, implement methods to optimize performance, and help define the product profile from a bioinformatics perspective, with input from R&D, Product, and Laboratory Directors.

Primary Responsibilities:

Team Leadership and Development: Lead and mentor a team of Bioinformatics Scientists. Own their professional growth, their responsibilities, and the standard the team holds itself to.

Research Strategy: Own the research strategy behind new product development, from scoping through execution, working with cross-functional stakeholders on what the team takes on and in what order.

Assay Science: Lead bioinformatics analysis for assay development and optimization, and troubleshoot experiments alongside laboratory scientists. This spans multi-omic approaches including methylation and fragmentomics and other cell-free DNA (cfDNA) derived features. It also spans short-read and long-read sequencing and both hybrid-capture and amplicon target enrichment.

Study Design and Data Quality: Partner with laboratory teams on study design at the research and feasibility stage, covering new technology assessment, optimization, and performance determination. Make sure the resulting data holds up before anyone builds on it.

Analysis Method Improvement: Advise and prototype improvements to analysis pipelines, including variant detection, quality control, and modality-specific processing: methylation calling, fragment-size and end-motif analysis, error suppression for deep targeted panels, and structural-variant calling.

Production Readiness and Handoff: Move research prototypes into stable production workflows. Hold the team to software engineering practice, including version control, testing, continuous integration and delivery, and containerization. Automate the routine parts of research data management, pipeline execution, and reporting so the team's time goes to science.

Ways of Working: AI is a routine part of the work here. As the leader of this team you set what correct use looks like: what an agent may conclude on its own, and what requires a scientist to sign off. We do not screen for prior experience with these tools, and many strong candidates come from environments where they were restricted; we provide the tooling and the ramp time.

Cross-functional Partnership: Work with data science, molecular biology, pipeline engineering, biostatistics, quality assurance, and laboratory operations on new products and on the transition of research work into production. Act as the subject-matter expert those groups come to, and explain findings and the roadmap clearly at every level of the company.

What success looks like after a year:
  • The team has a research roadmap you own, and progress against it is visible outside the team.
  • You independently advise and guide research strategies in cross functional settings.
  • New analysis methods from your team are implemented within production code and demonstrate expected performance on benchmark studies..
  • You and team members become trusted experts that other functions direct their hard questions to, and can independently support decision making.
  • AI agent-assisted work is normal on the team, with a standard for it that you set.
Qualifications:
  • Ph.D. in Bioinformatics, Computational Biology, Computer Science, Mathematics, Engineering, Biostatistics, or a related field. (An M.S. with equivalent experience considered).
  • 7+ years in bioinformatics, including 3+ years leading scientists and working across functions.
  • Demonstrated ownership of a team that took scientific research into real clinical use, not only to a result.
  • Demonstrated experience developing or scientifically guiding diagnostic sequencing assays.
Knowledge, Skills, and Abilities:What we are screening for
  • Deep expertise in next-generation sequencing analysis: hybrid-capture or amplicon-based target enrichment designs, sequencing quality control, secondary analysis, and variant calling.
  • Experience with cell-free DNA sequencing and other omics data, especially in a diagnostics setting. Preferred to have some exposure to multiomics types : methylation, fragmentomics, or related cfDNA signals.
  • Working  knowledge of how a diagnostic product moves through development in a regulated, accredited setting, including the practices and standards that apply.
  • Strong Python, programming, and data analysis skills.
  • Fluency in exploratory data analysis and visualization on complex data sets, and the ability to translate findings into actionable recommendations.
  • Understanding of sequencing workflows from sample extraction through the instrument, deep enough to tell a biology problem from an analysis problem.
  • A demonstrated record of assessing a new platform, assay chemistry or method against established benchmarks..
  • Clear communication of technical detail to people who do not share your background.
  • The ability to run several objectives and timelines at once without close supervision.
Strong candidates may also have
  • Long-read sequencing (PacBio HiFi, Oxford Nanopore) in addition to short-read (Illumina).
  • R, shell scripting, or Java.
  • Cloud computing (AWS, GCP) and workflow orchestration (Snakemake, WDL, Nextflow, Cromwell).
  • Containerization (Docker, Kubernetes) for reproducible, production-grade analyses.
  • A record of conference presentations or peer-reviewed publication.
  • A desire to work in a fast-paced environment where a small team has high impact.

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