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Bioinformatics Data Analyst Jobs in Portland, OR

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Bioinformatics Data Analyst information

See Portland, OR salary details

$7

$48

$87

How much do bioinformatics data analyst jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for bioinformatics data analyst in Portland, OR is $48.75, according to ZipRecruiter salary data. Most workers in this role earn between $38.37 and $52.16 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Bioinformatics Data Analyst, and why are they important?

To thrive as a Bioinformatics Data Analyst, a solid background in biology, statistics, and programming (often with a degree in bioinformatics, computational biology, or a related field) is essential. Proficiency with tools such as R, Python, SQL, and bioinformatics software like BLAST or Bioconductor, as well as experience with large datasets and relevant certifications, is typically required. Strong analytical thinking, attention to detail, and effective communication skills help analysts interpret complex data and collaborate with interdisciplinary teams. These skills ensure accurate data analysis, meaningful biological insights, and successful project outcomes in research or clinical settings.

What is the difference between Bioinformatics Data Analyst vs Bioinformatics Scientist?

AspectBioinformatics Data AnalystBioinformatics Scientist
Required CredentialsBachelor's or Master's in Bioinformatics, Biology, or related fieldsMaster's or PhD in Bioinformatics, Computational Biology, or related fields
Work EnvironmentData analysis teams, research labs, healthcare settingsResearch projects, development of algorithms, scientific publications
Employer & Industry UsageBiotech companies, healthcare institutions, research organizationsAcademic institutions, biotech firms, pharmaceutical companies
Common Search & ComparisonOften compared for data analysis roles in bioinformaticsMore research-focused, involved in algorithm development

Bioinformatics Data Analysts primarily focus on analyzing biological data using existing tools, while Bioinformatics Scientists develop new algorithms and conduct research. Both roles require strong computational skills, but the Scientist role typically involves more advanced research and innovation.

How do Bioinformatics Data Analysts typically collaborate with researchers and other team members in a multidisciplinary environment?

Bioinformatics Data Analysts often work closely with biologists, clinicians, and software engineers, acting as a bridge between experimental research and computational analysis. Collaboration usually involves interpreting experimental data, discussing analytical approaches, and presenting findings in a way that's accessible to non-technical stakeholders. Regular team meetings and project updates are common, and strong communication skills are essential for translating complex data insights into actionable information for the broader research team. This multidisciplinary teamwork fosters innovation and ensures that analyses align with the goals of larger research projects.

What are Bioinformatics Data Analysts?

Bioinformatics Data Analysts are professionals who use computational tools and methods to analyze biological data, such as genomic sequences or protein structures. They work at the intersection of biology, computer science, and statistics to interpret complex datasets and draw meaningful insights for research or clinical applications. Their work supports areas like drug discovery, personalized medicine, and evolutionary biology. Typically, they collaborate with biologists, software engineers, and statisticians to solve complex biological problems. Strong analytical skills and proficiency with data analysis software are essential for this role.
What are popular job titles related to Bioinformatics Data Analyst jobs in Portland, OR? For Bioinformatics Data Analyst jobs in Portland, OR, the most frequently searched job titles are:
Infographic showing various Bioinformatics Data Analyst job openings in Portland, OR as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $101,401 per year, or $48.8 per hour.

Bioinformatics Scientist - Gene Regulation & Cellular Reprogramming

e184

Portland, OR

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 4 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 youll 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.

Youll 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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