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Bioinformatics Analyst Jobs (NOW HIRING)

Experience Required 7+ Years Position Overview We are seeking a highly skilled Bioinformatics Analyst III to support biomedical and clinical research data initiatives. The ideal candidate will have ...

Experience Required 7+ Years Position Overview We are seeking a highly skilled Bioinformatics Analyst III to support biomedical and clinical research data initiatives. The ideal candidate will have ...

Experience Required 7+ Years Position Overview We are seeking a highly skilled Bioinformatics Analyst III to support biomedical and clinical research data initiatives. The ideal candidate will have ...

We are seeking a talented Bioinformatics Analyst to join our dynamic, multi-disciplinary team that is responsible for implementing and aiding in design and analysis software and informatics pipelines ...

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Bioinformatics Analyst information

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How much do bioinformatics analyst jobs pay per hour?

As of Jun 7, 2026, the average hourly pay for bioinformatics analyst in the United States is $45.82, according to ZipRecruiter salary data. Most workers in this role earn between $36.06 and $49.04 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.
What cities are hiring for Bioinformatics Analyst jobs? Cities with the most Bioinformatics Analyst job openings:
What are the most commonly searched types of Bioinformatics Analyst jobs? The most popular types of Bioinformatics Analyst jobs are:
Who are the top companies hiring for Bioinformatics Analyst jobs? The top employers for Bioinformatics Analyst jobs are:
What states have the most Bioinformatics Analyst jobs? States with the most job openings for Bioinformatics Analyst jobs include:
Infographic showing various Bioinformatics Analyst job openings in the United States as of May 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 80% Physical, 2% Hybrid, and 18% Remote job distribution, with an average salary of $95,308 per year, or $45.8 per hour.
Bioinformatics Analyst

Bioinformatics Analyst

Albert Einstein College of Medicine

Bronx, NY โ€ข On-site, Remote

$65K/yr

Full-time

Posted yesterday


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.