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Bioinformatics Analyst information

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$7

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$87

How much do bioinformatics analyst jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for bioinformatics analyst in Portland, OR is $48.59, according to ZipRecruiter salary data. Most workers in this role earn between $38.22 and $52.02 per hour, depending on experience, location, and employer.

What does a bioinformatics analyst do?

A bioinformatics analyst works with large databases of omics data, such as genomics studies like the Human Genome Project. Your responsibilities in this career include research on the pathology of diseases and the development of experiments and algorithms to find cures. Your duties also involve ensuring compliance with all federal regulations and protocols. You may document your findings and present them at conferences as well. A career as a bioinformatics analyst requires advanced writing skills for writing scientific literature.

What is the difference between Bioinformatics Analyst vs Bioinformatics Technician?

AspectBioinformatics AnalystBioinformatics Technician
Required CredentialsBachelor's or Master's in Bioinformatics, Biology, or related field; experience with data analysis toolsAssociate's or Bachelor's; focus on data processing and laboratory support
Work EnvironmentResearch labs, biotech companies, healthcare institutionsLaboratories, research facilities, academic settings
Employer & Industry UsageUsed in research, healthcare, biotech industries for data interpretationUsed for data collection, sample processing, and technical support roles

The main difference is that Bioinformatics Analysts focus on analyzing complex biological data and interpreting results, often requiring advanced degrees. Bioinformatics Technicians typically handle data collection, sample preparation, and technical tasks, supporting analysts and researchers. Both roles are essential in the biotech and healthcare industries, but they differ in responsibilities and required qualifications.

What are some common challenges faced by bioinformatics analysts when working with large genomic datasets?

One of the main challenges Bioinformatics Analysts encounter is managing and processing extremely large and complex genomic datasets, which often require advanced computational resources and efficient data management strategies. Ensuring data quality and accuracy while integrating information from various sources can also be demanding. Analysts frequently collaborate with biologists, clinicians, and IT professionals to interpret results and optimize workflows, which requires strong communication and interdisciplinary skills.

What does a bioinformatics analyst do?

A Bioinformatics Analyst uses computational and statistical methods to analyze biological data, such as DNA, RNA, or protein sequences. They interpret large datasets generated by experiments, develop algorithms, and create visualizations to help researchers understand complex biological processes. Their work supports scientific discoveries in fields like genomics, medicine, and agriculture, often collaborating with biologists, computer scientists, and other researchers.

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

To thrive as a Bioinformatics Analyst, you need a strong background in biology, statistics, and computer science, typically supported by a relevant bachelor's or master's degree. Familiarity with bioinformatics tools like BLAST, Python/R programming, and experience with databases such as GenBank or Ensembl are commonly required. Analytical thinking, problem-solving, and effective communication are crucial soft skills for interpreting data and collaborating with multidisciplinary teams. These skills enable analysts to extract meaningful insights from complex biological data, driving research and innovation in genomics and healthcare.
More about Bioinformatics Analyst jobs
What are the most commonly searched types of Bioinformatics Analyst jobs in Portland, OR? The most popular types of Bioinformatics Analyst jobs in Portland, OR are:
What are popular job titles related to Bioinformatics Analyst jobs in Portland, OR? For Bioinformatics Analyst jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Bioinformatics Analyst jobs in Portland, OR look for? The top searched job categories for Bioinformatics Analyst jobs in Portland, OR are:
Bioinformatics Analyst jobs near you
Infographic showing various Bioinformatics Analyst job openings in Portland, OR as of July 2026, with employment types broken down into 84% Full Time, 10% Part Time, 1% Temporary, and 5% Contract. Highlights an 81% Physical, 7% Hybrid, and 12% Remote job distribution, with an average salary of $98,579 per year, or $47.4 per hour.

Bioinformatics Scientist - Gene Regulation & Cellular Reprogramming

e184

Portland, OR • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 12 days ago

Job description

About us
e184 Repro is a biotechnology research company with the mission of advancing in vitro gametogenesis to solve one of biology's most profound challenges: returning the fundamental right to procreate.
We work at the frontier of cutting-edge technology, integrating cellular reprogramming, machine learning-guided optimization, multi-omics analysis, and automated experimental workflows to enable gamete development for individuals facing reproductive challenges.
Role overview
As a Bioinformatics Scientist with a cellular reprogramming background, you will lead computational analysis of multi-modal genomics data (scRNA-seq, ATAC-seq) to identify transcription factor combinations driving desired cell state conversion. This role focuses on gene regulatory network inference, differential analysis of single-cell transcriptomics, and computational prioritization of TF cocktails for cellular reprogramming, requiring deep expertise in multi-platform scRNA-seq analysis and transcriptional regulation biology. You will collaborate closely with wet lab teams to translate computational predictions into experimental designs, while also exploring hybrid approaches that integrate foundation model insights into our reprogramming pipeline.
What you'll do
  • Lead end-to-end TF discovery for cellular reprogramming - from multi-platform single-cell genomics analysis (scRNA-seq, ATAC-seq) through GRN inference, differential analysis, and trajectory mapping - to nominate the regulators that flip cell fate.
  • Crack the combinatorial code of reprogramming by ranking TF cocktails as actionable combinations and decoding pooled perturbation and CRISPRa screens at single-cell resolution.
  • Read regulatory grammar straight off the chromatin - accessibility, motifs, synergy, repression - and build the data backbone that harmonizes modalities and platforms into something we can actually model on.
  • Sit shoulder-to-shoulder with wet lab teammates, closing the loop between predictions and screens: ingest fresh NGS readouts, retrain, re-prioritize, and pick the next experiment that teaches the model the most.

Core requirements
  • PhD in Bioinformatics, Computational Biology, or related quantitative field (or MS with 5+ years relevant industry experience);
  • Demonstrated track record applying computational TF ranking and GRN inference to cellular reprogramming problems, transdifferentiation, directed differentiation, or iPSC systems;
  • Multi-platform single-cell RNA-seq expertise: hands-on analysis from at least two different platforms, including platform-specific troubleshooting and quality control;
  • Multi-modal genomics proficiency: ChIP-seq, CUT&RUN, or ATAC-seq analysis including peak calling, differential accessibility, and TF motif enrichment;
  • Hands-on experience with established GRN inference methods to nominate or rank regulators of cell state, beyond literature-curated lists;
  • Experience analyzing pooled perturbation screens (CRISPRa, CRISPR knockout, or barcoded TF overexpression) with single-cell or bulk readouts;
  • Working knowledge of trajectory inference and pseudotime methods for mapping cell state transitions;
  • Strong programming skills in Python and R, with proficiency in Scanpy/Seurat and statistical analysis for high-dimensional data;
  • Comfortable working in a modern computational environment: cloud platforms, workflow managers, containerization, and collaborative version control;
  • Strong publication record and demonstrated cross-functional collaboration with experimental biologists.

You'll stand out with
  • Direct experience nominating or validating TF cocktails that successfully induced a cell state conversion (published or in preparation).
  • Experience with dynamical systems modeling for cell state transitions, or inverse problem approaches for TF combination ranking.
  • Background in advanced trajectory inference (optimal transport, GRN dynamics over pseudotime), Bayesian genomics, multi-omics integration, or cross-species comparative regulatory genomics.
  • Familiarity with transformer architectures in genomics and interest in hybrid classical/ML approaches to gene regulation.

Why e184?
  • Unrivaled impact: Your work directly enables technology that transforms human fertility and reproductive medicine.
  • Full-spectrum growth: Gain exposure to the entire lifecycle of discovery. From screening to mechanistic validation.
  • Best of both worlds: Experience the creative chaos of an early-stage startup with the stability of a well-capitalized company.
  • Elite collaboration: Work alongside a world-class team who are as driven as you are.

What we offer
  • Competitive salary + equity participation is considered
  • State-of-the-art facility in Portland metro area
  • Comprehensive Medical, Dental, Vision, and 401(k) with company match
  • 20 days PTO + 11 paid holidays

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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