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Remote Bioinformatics Jobs in Oregon (NOW HIRING)

In this role, you will build the bioinformatics capability within the Data Science development team, establish scalable AWS cloud infrastructure, and ensure the quality and reproducibility of the ...

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Natera is seeking an innovative and driven bioinformatics scientist to lead and conduct cutting-edge real-world evidence (RWE) analyses and predictive analytics across oncology, organ health, and ...

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... bioinformatics, and cheminformatics methods. * Curate, annotate, and validate chemical and ...

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Showing results 1-20

Remote Bioinformatics information

See Oregon salary details

$62.9K

$99.9K

$158.1K

How much do remote bioinformatics jobs pay per year?

As of Aug 24, 2026, the average yearly pay for remote bioinformatics in Oregon is $99,886.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,400.00 and $136,900.00 per year, depending on experience, location, and employer.

What is remote bioinformatics?

A Remote Bioinformatics job involves analyzing biological data using computational tools and techniques while working from a location outside of a traditional office, such as from home. Professionals in this field work with large datasets, develop algorithms, and create software to interpret genetic, genomic, or proteomic information. These roles are commonly found in research institutions, biotech companies, and healthcare organizations. Strong programming, data analysis, and biological domain knowledge are essential for success in this role.

What are the key skills and qualifications needed to thrive in remote bioinformatics?

To thrive as a Remote Bioinformatics professional, you should have a strong background in computational biology, statistics, and programming (often with languages such as Python or R), supported by an advanced degree in a relevant field. Familiarity with bioinformatics tools (e.g., BLAST, GATK, Bioconductor), version control systems like Git, and experience with cloud-based computing platforms is highly valued. Excellent problem-solving abilities, clear written communication, and independent time management skills help you excel in remote and collaborative environments. These competencies are crucial for delivering accurate and timely insights from complex biological datasets while effectively working with geographically dispersed teams.

What are some typical challenges faced when working remotely in bioinformatics?

Working remotely in bioinformatics often means managing large datasets and complex analyses without immediate in-person support, which requires strong troubleshooting abilities and self-sufficiency. Collaborating with cross-disciplinary teams—such as biologists, clinicians, and data scientists—demands proactive communication and regular virtual meetings to ensure project alignment. Time zone differences and asynchronous workflows can also present coordination challenges, but they offer flexibility in managing your workload. Keeping up with the latest bioinformatics tools and research is essential and often involves continuous self-directed learning. With these factors in mind, remote bioinformatics roles can be both rewarding and flexible for those skilled at independent work and digital collaboration.

What are the most commonly searched types of Bioinformatics jobs in Oregon?

The most popular types of Bioinformatics jobs in Oregon are:

What are popular job titles related to Remote Bioinformatics jobs in Oregon?

For Remote Bioinformatics jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Remote Bioinformatics jobs in Oregon look for?

The top searched job categories for Remote Bioinformatics jobs in Oregon are:

What cities in Oregon are hiring for Remote Bioinformatics jobs?

Cities in Oregon with the most Remote Bioinformatics job openings:

Infographic showing various Remote Bioinformatics job openings in Oregon as of August 2026, with employment types broken down into 60% Full Time, 39% Part Time, and 1% Contract. Highlights an 51% Physical, 3% Hybrid, and 46% Remote job distribution, with an average salary of $99,886 per year, or $48 per hour.

Director of Data Science and Bioinformatics

OR • On-site, Remote


Natera
Biotechnology Research and Development • 1 - 5K employees

7.7

Company rating: 7.7 out of 10

Based on 38 frontline employees who took The Breakroom Quiz

57th of 120 rated laboratories

People enjoy working here

Good employer

Paid breaks


Full-time

Posted 10 days ago


Job description

This is an exciting opportunity to lead and grow the Data Science and Bioinformatics function supporting Natera's Women's Health and Organ Health product portfolios. In this role, you will build the bioinformatics capability within the Data Science development team, establish scalable AWS cloud infrastructure, and ensure the quality and reproducibility of the genomic algorithms powering our clinical products.

PRIMARY RESPONSIBILITIES:

Strategy and Vision

  • Build and define the Bioinformatics function within the Data Science development team, identify technical tooling gaps, and execute a roadmap to advance genomics-based algorithm development.
  • Establish and enforce pipeline and algorithm quality standards, including review processes, validation frameworks, and documentation practices

Infrastructure and Automation

  • Own and architect scalable AWS-based data science and bioinformatics infrastructure, ensuring quality, reproducibility, and reliable deployment of Next-Generation Sequencing (NGS) algorithms.
  • Implement MLOps tooling and automated validation frameworks to support reliable algorithm deployment into clinical production.

Cross-Functional Collaboration

  • Partner with Research, Product Development, Laboratory Operations, Engineering, and Quality teams to implement stable, scalable pipelines and support successful productization

Team Leadership

  • Lead, mentor and hire a high-performing team of bioinformaticians and data scientists, establishing technical quality standards and clear operational ownership.
  • Build technical depth within the team to support expanding product roadmaps across Women's Health and Organ Health.

QUALIFICATIONS:

  • Master of Science or Ph.D. in a quantitative technical discipline (Biostatistics, Bioinformatics, Computer Science, Physics, Applied Mathematics, or equivalent).
  • Minimum of 10 years of experience in Data Science or Bioinformatics, with at least 5 years of direct people management experience leading technical teams.
  • Hands-on experience architecting AWS cloud infrastructure for data-intensive bioinformatics workloads and NGS pipeline execution.
  • Demonstrated ability to identify capability gaps independently, build scalable infrastructure, and drive execution without waiting for formal structure.
  • Strong communicator who builds cross-functional alignment across Research, Engineering, and Quality teams through technical clarity, direct engagement, and data-driven reasoning.
  • Track record of developing bioinformatics talent and delivering computational pipelines that support commercial product development.

PREFERRED QUALIFICATIONS:

  • Experience developing software and pipelines within regulated environments (CLIA, FDA, or ISO framework).
  • Experience with MLOps frameworks and pipeline tools (MLflow, Nextflow, WDL, Docker).
  • Advanced knowledge of statistical inference, machine learning, and genomic data processing.


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