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Bioinformatic Analyst Jobs in Oregon (NOW HIRING)

Lead the analysis of large-scale cancer and germline multi-omics datasets to extract meaningful insights. Utilize and augment traditional bioinformatics tools with AI-driven techniques to interpret ...

Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

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Bioinformatic Analyst information

See Oregon salary details

$32.8K

$77.5K

$137.4K

How much do bioinformatic analyst jobs pay per year?

As of Aug 24, 2026, the average yearly pay for bioinformatic analyst in Oregon is $77,458.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,500.00 and $92,000.00 per year, depending on experience, location, and employer.

What does a bioinformatic analyst do?

A Bioinformatic Analyst uses computational tools and techniques to analyze biological data, such as DNA, RNA, or protein sequences. They work closely with researchers and scientists to interpret complex datasets, identify patterns, and draw meaningful conclusions that can advance scientific understanding or medical research. Their responsibilities may include processing raw data, developing algorithms, and creating visualizations to present results. Bioinformatic Analysts often work in fields like genomics, pharmaceuticals, and biotechnology.

What are the key skills and qualifications needed to thrive as a bioinformatic analyst?

To thrive as a Bioinformatic Analyst, you need a strong background in biology, statistics, and computer science, often supported by a relevant degree such as bioinformatics, computational biology, or a related field. Proficiency in programming languages like Python or R, experience with next-generation sequencing (NGS) data analysis tools, and familiarity with databases such as GenBank are typically required. Critical thinking, attention to detail, and effective communication skills help analysts interpret complex data and collaborate with interdisciplinary teams. These skills are crucial for extracting meaningful insights from biological data and advancing research or clinical objectives.

What are some common challenges a bioinformatic analyst faces when working with large-scale genomic data?

One of the primary challenges for Bioinformatic Analysts is managing and analyzing massive datasets generated by next-generation sequencing technologies. Ensuring data quality, handling data storage, and optimizing computational resources are critical aspects of the role. Analysts must also develop or adapt pipelines to process complex data efficiently and accurately, often collaborating closely with biologists, statisticians, and IT specialists. Staying updated on rapidly evolving tools and best practices is essential to ensure high-quality, reproducible results.

Is bioinformatic analyst a stressful job?

Bioinformatic analysts often work in research or healthcare settings, analyzing large datasets and developing computational tools, which can involve tight deadlines and complex problem-solving. The level of stress varies depending on workload, project deadlines, and workplace environment, but the role generally requires strong attention to detail and technical skills. Managing workload and staying organized can help reduce stress in this position.

Is bioinformatics well paying?

Bioinformatic analysts typically earn competitive salaries that vary by experience, education, and location. In general, the field offers above-average pay compared to many other entry-level science roles, especially for those with advanced skills in programming, data analysis, and familiarity with tools like R or Python.

What cities in Oregon are hiring for Bioinformatic Analyst jobs?

Cities in Oregon with the most Bioinformatic Analyst job openings:

Infographic showing various Bioinformatic Analyst job openings in Oregon as of August 2026, with employment types broken down into 85% Full Time, 10% Part Time, and 5% Contract. Highlights an 79% Physical, 8% Hybrid, and 13% Remote job distribution, with an average salary of $77,458 per year, or $37.2 per hour.

Lead Bioinformatician (cfDNA Algorithms and Pipelines)

Natera

OR • On-site, Remote

Full-time

Posted 14 days ago


Natera rating

7.7

Company rating: 7.7 out of 10

Based on 38 frontline employees who took The Breakroom Quiz

57th of 120 rated laboratories


Job description

Natera is seeking a Lead Bioinformatician to advance the algorithmic foundations of our diagnostic assays supporting Women's and Organ health. This is an individual contributor role. You will bring the genomics expertise the team needs to pull reliable signals out of sequencing data that is often ambiguous.

You will build the methodological foundations and implement the algorithms needed for detecting variants (SNVs, Indels, CNVs, SVs) that are hard to call accurately in low fraction (fetal, donor cfDNA) samples. The ideal candidate will have deep experience in algorithmic genomics, strong programming skills, and a passion for developing scalable, clinically impactful computational tools.

Primary Responsibilities:

Panel and Assay Science: Provide genomics algorithm insights to our expanded panel roadmap, including which genes are worth considering and why, working with Product, the Laboratory Directors, and Research, who own that decision jointly. Help define the approach for analytically difficult genes and assay edge cases, and weigh what is scientifically defensible against what is technically possible.

Caller Strategy and Method Development: Define the computational strategy for new targeted and special-purpose callers. Help decide when a new caller is justified and when an existing method should be extended instead. Prototype and benchmark new methods, and work with the engineering team to get methods into production.

Scientific Investigation and Escalation: Serve as a genomics consultant on complex production escalations, separating biological causes from analytical and pipeline ones. Recognize when a result looks suspicious because of where the reads came from and not because the analysis went wrong. Turn one-off investigations into durable rules and design changes that reduce repeat work.

Data Quality and Cross-functional Partnership: Act as bioinformatics liaison with Variant Management, Reporting, and Laboratory Operations on data quality, variant representation, and system integration. Provide the scientific rationale that the accountable Quality and Laboratory functions rely on when they decide a method is ready to deploy.

Ways of Working: Help define what correct looks like for AI-assisted scientific investigation, for example what an agent may and may not conclude from a region-level finding without a human signing 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.

What success looks like after a year:
  • Contributed to the scientific and bioinformatics rationale of product roadmaps.
  • Deployment-readiness criteria for new analysis methods exist and are in use, and you have contributed to at least one new or extended caller yourself.
  • You take on the bioinformatics aspects inside complex production investigations without waiting to be assigned them.
  • Other groups know they can bring genomics questions about our assays to you.
Qualifications:
  • Degree in Bioinformatics, Computational Biology, Bioinformatics, Human Genetics, or a related field. We do not require a Ph.D. or M.S.: equivalent depth built through work counts fully.
  • 4+ years analyzing short-read sequencing data for screening or diagnostic applications, preferably in a regulated, accredited, or production-adjacent setting. We count relevant experience from the point your work became substantially independent, however you got there.
  • Experience contributing to the bioinformatics workflows behind a sequencing assay or panel.
  • Experience seeing a complex investigation through to resolution across biological, analytical, and systems-level causes.
Knowledge, Skills, and Abilities:What we are screening for
  • Experience developing, validating, or benchmarking bioinformatics methods (e.g. SNVs, CNVs, SVs), particularly for analytically difficult regions.
  • Proficient in Python with demonstrated experience prototyping bioinformatics tools or callers.
  • Enough human genetics depth to contribute to the panel design: variant spectrum, population frequency, and where compromises on accuracy can (and cannot) be made.
  • Familiarity with identifying regions where short reads cannot be placed with confidence: homologous sequence and pseudogenes, low-complexity and repeat structure, and copy-number-heavy regions.
  • Experience contributing to study designs or performance criteria for a bioinformatics analysis method.
Strong candidates may also have
  • Direct non-invasive prenatal, reproductive, or carrier screening experience.
  • Experience with cfDNA, or with another application where the molecules you care about are a small minority of what was sequenced.
  • Experience developing algorithms for both short-read and long-read sequencing platforms (e.g., Illumina, ONT, PacBio).
  • Cross-functional credibility with genetic counseling, variant management, reporting, and production-adjacent groups.
  • Experience in an accredited or high-complexity laboratory, or familiarity with production support or escalation processes.

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