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Clinical Bioinformatics Analyst Jobs (NOW HIRING)

Cincinnati Children's

Bioinformatics Analyst

Burnet, TX · On-site

$61.40K - $78.29K/yr

We are seeking a highly motivated Bioinformatics Analyst / Web Developer who is passionate about ... Interfaces with clinicians/researchers to collect requirements of basic to moderate complexity ...

Oran Inc

Bioinformatics Analyst III

Herndon, VA · On-site

Support biomedical and clinical research data analysis initiatives. * Analyze structured and ... Bachelor's or Master's degree in Bioinformatics, Computational Biology, Biomedical Informatics ...

Oran Inc

Bioinformatics Analyst III

Herndon, VA

Support biomedical and clinical research data analysis initiatives. * Analyze structured and ... Bachelor's or Master's degree in Bioinformatics, Computational Biology, Biomedical Informatics ...

Oran, Inc.

Bioinformatics Analyst III

Herndon, VA · On-site

Support biomedical and clinical research data analysis initiatives. * Analyze structured and ... Bachelor's or Master's degree in Bioinformatics, Computational Biology, Biomedical Informatics ...

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How much do clinical bioinformatics analyst jobs pay per hour?

As of May 28, 2026, the average hourly pay for clinical bioinformatics analyst in the United States is $39.80, according to ZipRecruiter salary data. Most workers in this role earn between $31.49 and $45.67 per hour, depending on experience, location, and employer.

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

To thrive as a Clinical Bioinformatics Analyst, you need a solid background in molecular biology, genetics, and bioinformatics, often supported by a relevant degree such as bioinformatics or computational biology. Familiarity with tools like Python, R, next-generation sequencing (NGS) analysis platforms, and experience with clinical databases are commonly required, along with certifications in genomics or data analysis as a plus. Strong analytical thinking, problem-solving abilities, and effective communication are essential soft skills for interpreting complex data and collaborating with healthcare teams. These skills ensure accurate analysis and interpretation of genomic data, directly impacting patient diagnosis, treatment decisions, and clinical research outcomes.

What are common challenges faced by Clinical Bioinformatics Analysts when integrating genomic data into clinical workflows?

Clinical Bioinformatics Analysts often encounter challenges such as ensuring the accuracy and consistency of complex genomic datasets, adhering to strict data privacy regulations, and translating bioinformatics findings into actionable insights for clinicians. Collaboration with multidisciplinary teams—including genetic counselors, clinicians, and IT specialists—is essential to address data interpretation and integration hurdles. Staying up-to-date with evolving bioinformatics tools and clinical guidelines is also crucial for delivering reliable results in a fast-paced healthcare environment.

What does a Clinical Bioinformatics Analyst do?

A Clinical Bioinformatics Analyst is responsible for analyzing and interpreting complex biological data, particularly genetic and genomic information, to support clinical diagnostics and patient care. They use advanced computational tools and software to process sequencing data, identify genetic variants, and help clinicians understand the implications for disease diagnosis, prognosis, and treatment. Their work bridges the gap between laboratory science and clinical application, ensuring that genomic findings are accurately translated into actionable medical information.
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Clinical Bioinformatics Analyst jobs near you
Bioinformatics Analyst

Bioinformatics Analyst

Albert Einstein College of Medicine

Bronx, NY • On-site, Remote

$65K/yr

Full-time

Posted 21 days ago

Job description

About Us
We are seeking a highly motivated Bioinformatics Analyst to join the research group of Dr. Robert Burk at Albert Einstein College of Medicine. Our group conducts molecular epidemiology and microbiome research with an emphasis on the human microbiome (cervicovaginal, oral, and gut) and HPV-related neoplasia. This role is central to translating large-scale sequencing datasets into rigorous, publication-ready results with direct relevance to chronic disease, cancer prevention and infectious disease research. Our work has been published in high-impact journals such as Nature Communications and Cell. The ideal candidate is an independent problem solver who is comfortable taking ownership of analysis workstreams, building and maintaining reproducible pipelines, and driving projects forward from raw data to interpretable outputs. They should be collaborative, communicate clearly with wet lab and epidemiology teams, and proactively propose analytic approaches that strengthen the science and accelerate progress.
POSITION RESPONSIBILITIES
  • Pipeline development and leadership: Design, implement, document, and maintain end-to-end NGS pipelines for microbiome and HPV genomics applications (e.g., 16S/ITS1 amplicon sequencing, shotgun metagenomics, viral/HPV sequencing, bisulfite sequencing, and viral integration analyses).
  • Large-scale data processing: Perform robust QC, read processing, reference alignment, taxonomic and functional profiling, strain-level analyses where appropriate, and reproducible reporting for cohort-scale datasets.
  • Clinical and epidemiologic integration: Harmonize sequencing outputs with clinical and epidemiologic metadata (including complex longitudinal designs), perform data cleaning and validation, and generate analysis-ready tables.
  • Statistical and computational analysis: Conduct and interpret statistical analyses using R and/or Python, including microbiome-specific methods (alpha/beta diversity, ordination, PERMANOVA, differential abundance) and epidemiologic modeling (regression and related approaches), with publication-quality visualizations.
  • Project leadership and communication: Lead defined analysis workstreams, set realistic milestones, communicate risks and dependencies early, and present progress and results in lab meetings and to collaborators.
  • Troubleshooting and optimization: Diagnose and resolve complex issues (pipeline failures, batch effects, contamination artifacts, inconsistent metadata, compute bottlenecks). Improve robustness, scalability, and runtime efficiency on shared compute environments.
  • Reproducibility and best practices: Use version control (Git), structured documentation, and reproducible execution practices (workflow managers and/or containerization when appropriate). Maintain clear provenance from raw data to results.
  • Scientific contribution: Propose fresh analytic ideas, evaluate new tools and methods, and contribute to interpretation and narrative framing of findings.
  • Manuscripts and grants: Contribute figures, methods text, and analyses for manuscripts and grant applications.

QUALIFICATIONS
Required:
  • Bachelor's degree in bioinformatics, computational biology, biostatistics, epidemiology, computer science, or a related field; Master's or PhD preferred.
  • Strong programming ability in R and/or Python, plus comfort working in a Unix/Linux environment (shell scripting, HPC-style workflows).
  • Demonstrated experience processing and analyzing NGS data, including building or extending pipelines rather than only running existing ones.
  • Solid understanding of basic statistical concepts and the ability to translate scientific questions into appropriate analyses.
  • Track record of independent problem solving, attention to detail, and producing reliable, well-documented outputs.
  • Strong communication skills and a collaborative mindset for working with interdisciplinary teams.

Preferred:
  • Experience in microbiome bioinformatics (16S, ITS1, shotgun metagenomics) and/or viral genomics with familiarity with phylogenetics, or integration-related analyses.
  • Experience working with protected clinical or epidemiologic data and with best practices for data security and governance.
  • Experience analyzing large cohorts and handling confounding, batch effects, and complex study designs (longitudinal, nested case-control, matched studies).
  • Comfort translating analyses into clear figures, methods, and results text suitable for high-impact manuscripts

Practical Experience: The candidate is expected to have practical experience with bioinformatics work (handling NGS reads off the machine, etc.) and be willing and eager to adapt to new approaches. This role will be facilitated with a proactive attitude towards learning and applying new bioinformatics methods and technologies.
Additional Information
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is listed below. Albert Einstein College of Medicine considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer.
Maximum Salary Range
USD $65,000.00/Yr.

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