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Variant Scientist Jobs in Oregon (NOW HIRING)

Natera

OR · On-site

... robust performance for variant calling, fusion detection, and automated quality control ... PhD in Bioinformatics, Computer Science, Engineering, Statistics, Cancer Biology or similar field ...

PacBio

OR

$93K - $140K/yr

Scientist II, Field Applications Bioinformatics Support PacBio (NASDAQ: PACB) is a premier life ... alignment, variant calling, de novo assembly, genome visualization, transcript mapping

Natera

OR

Natera is seeking an innovative and driven bioinformatics scientist to lead and conduct cutting ... Expert knowledge of bioinformatics tools including mapping, variant calling, CNV analysis and ...

Natera

OR

$126K - $166K/yr

... variant interpretation, clinical review, and reporting. As Natera scales across Women's Health ... Bachelor's degree in life sciences, engineering, computer science, statistics, or equivalent ...

Natera

OR

... performance, variant interpretation, software defects) * Support post-market surveillance ... Partner with engineering and data science teams to evaluate software-related complaints and ...

Netflix

OR · On-site

$388K - $619K/yr

In this role, you will partner closely with data scientists and other engineers to build low ... Scala) and SQL (any variant) You strive to write elegant and maintainable code, and you're ...

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Variant Scientist information

See Oregon salary details

$17

$46

$81

How much do variant scientist jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for variant scientist in Oregon is $46.93, according to ZipRecruiter salary data. Most workers in this role earn between $34.05 and $59.46 per hour, depending on experience, location, and employer.

What does a variant scientist do?

As a variant scientist, you work for a research laboratory in a university or a medical facility to test and study variations of genes and the effects they have on human development. As part of your duties, you aid in the development of new tests to discover gene abnormalities, perform analysis on patient samples to identify possible mutations, and record your findings to assist in scientific research. You also have heavy reporting responsibilities that may require in-depth computer and writing skills, the ability to analyze data, and strong attention to detail. In this role, you may cater to a specific health field, like pediatrics or oncology.

What are some common challenges faced by variant scientists in interpreting genetic data, and how are these typically addressed within a team?

Variant Scientists often encounter challenges such as distinguishing between benign and pathogenic variants, managing large volumes of sequencing data, and staying updated with rapidly evolving genetic databases. These challenges are typically addressed by collaborating closely with bioinformaticians, clinical geneticists, and laboratory personnel to review findings and validate interpretations. Regular team meetings, use of standardized classification guidelines like ACMG, and leveraging advanced software tools help ensure accurate and consistent variant analysis.

What is a variant scientist?

Variant Scientists are professionals who analyze genetic variants—differences in DNA sequences—to determine their significance in health and disease. They interpret genomic data, often from whole-genome or exome sequencing, to assess whether specific variants may cause or contribute to medical conditions. Their work is crucial in clinical genetics, precision medicine, and biomedical research, helping guide patient diagnosis and treatment. Variant Scientists collaborate with clinicians, bioinformaticians, and laboratory personnel to provide accurate and actionable genetic insights.

What are the key skills and qualifications needed to thrive as a variant scientist, and why are they important?

To thrive as a Variant Scientist, you need a solid background in genetics, molecular biology, and bioinformatics, typically supported by an advanced degree such as a PhD or MSc in a related field. Familiarity with next-generation sequencing (NGS) platforms, variant annotation tools, and data analysis software like GATK or ANNOVAR is essential. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex genetic data and collaborate with multidisciplinary teams. These skills ensure accurate variant interpretation, drive discoveries, and support precision medicine initiatives.
More about Variant Scientist jobs
What are the most commonly searched types of Variant Scientist jobs in Oregon? The most popular types of Variant Scientist jobs in Oregon are:
What are popular job titles related to Variant Scientist jobs in Oregon? For Variant Scientist jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Variant Scientist jobs in Oregon look for? The top searched job categories for Variant Scientist jobs in Oregon are:
What cities in Oregon are hiring for Variant Scientist jobs? Cities in Oregon with the most Variant Scientist job openings:
Variant Scientist jobs near you
Infographic showing various Variant Scientist job openings in Oregon as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 10% Part Time, 4% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $97,614 per year, or $46.9 per hour.

Senior Bioinformatics Scientist

Natera

OR • On-site

Full-time

Posted 10 days ago

Natera rating

7.6

Company rating: 7.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

60th of 120 rated laboratories

Job description

Natera is seeking a Senior Bioinformatics Scientist to join our Bioinformatics team dedicated to early cancer detection. As a core member of the Research and Development department, you will play a pivotal role in designing and implementing innovative computational solutions. The ideal candidate possesses a robust background in algorithm development, high-throughput biological data analysis, and scalable pipeline architecture. We are looking for a versatile professional capable of thriving as an individual contributor, a collaborative co-developer, and a key participant in large-scale, cross-departmental initiatives. In this role, you will develop novel algorithms and pipelines while analyzing complex genomic datasets to advance the frontiers of early-stage cancer diagnostics.
PRIMARY RESPONSIBILITIES:

  • Innovate, design, develop, and validate advanced algorithms and statistical models to extract actionable insights from large-scale genomic datasets for early cancer detection.
  • Co-architect, implement, and deploy automated analysis workflows for clinical diagnostics, ensuring robust performance for variant calling, fusion detection, and automated quality control.
  • Contribute to rigorous code reviews, maintain comprehensive technical documentation, and drive the continuous optimization of core computational infrastructure.
  • Analyze complex multi-omic data using high-performance internal pipelines, collaborating closely with wet-lab scientists and statisticians to meet critical research milestones.

QUALIFICATIONS:

  • PhD in Bioinformatics, Computer Science, Engineering, Statistics, Cancer Biology or similar field
  • 0-3 years of professional or postgraduate experience in bioinformatics or computational biology.

KNOWLEDGE, SKILLS AND ABILITIES:

  • Excellent communication skills with a demonstrated ability to present complex computational findings to diverse cross-functional stakeholders.
  • Deep expertise in high-throughput DNA sequencing (NGS) analysis, including sequence alignment, mapping, and clinical-grade variant calling.
  • A proven track record of developing state-of-the-art, high-impact bioinformatics methodologies.
  • Advanced knowledge of data structures, algorithm design, and computational complexity analysis.
  • High proficiency in Python and its scientific ecosystem (NumPy, Pandas, Scikit-learn) for data manipulation and automation.
  • Experience with workflow orchestration languages (WDL preferred) for building and versioning scalable bioinformatics pipelines.
  • Experience with cloud-based distributed computing environments, specifically AWS.
  • Familiarity with contemporary analytical techniques and biomarkers in cancer biology.
  • Working knowledge of public genomic databases such as TCGA, COSMIC, or OncoKB.
  • Proficiency in Linux environments, including command-line tools and shell scripting.

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