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Clinical Variant Analyst Jobs in Silver Spring, MD

Axle

Bioinformatics Scientist

Bethesda, MD

Provide bioinformatics support to include somatic and germline variant calling and analysis, single ... Perform computational data analysis on genomic and clinical research data. * Work with staff on ...

Axle

Bioinformatics Scientist

Bethesda, MD

Provide bioinformatics support to include somatic and germline variant calling and analysis, single ... Perform computational data analysis on genomic and clinical research data. * Work with staff on ...

Axle

Bioinformatics Scientist

Bethesda, MD · On-site

Provide bioinformatics support to include somatic and germline variant calling and analysis, single ... Perform computational data analysis on genomic and clinical research data. * Work with staff on ...

All JobsClinical Variant Analyst JobsClinical Variant Analyst Jobs in Silver Spring, MD

Clinical Variant Analyst information

See Silver Spring, MD salary details

$18

$41

$64

How much do clinical variant analyst jobs pay per hour?

As of Jun 16, 2026, the average hourly pay for clinical variant analyst in Silver Spring, MD is $41.15, according to ZipRecruiter salary data. Most workers in this role earn between $32.55 and $47.21 per hour, depending on experience, location, and employer.

What is a Clinical Variant Analyst?

A Clinical Variant Analyst is a professional who interprets and analyzes genetic variants identified through clinical genetic testing. Their main role is to evaluate DNA sequence changes to determine their significance in relation to health and disease. They collaborate with geneticists, laboratory scientists, and clinicians to classify variants according to established guidelines and help inform patient diagnoses and management. Additionally, Clinical Variant Analysts review scientific literature, use databases, and may contribute to research and quality improvement in genetic testing.

What are some common challenges Clinical Variant Analysts face when interpreting genetic data, and how can they be addressed?

Clinical Variant Analysts often encounter challenges such as distinguishing between benign and pathogenic variants, managing large datasets, and keeping up with rapidly evolving scientific literature. Addressing these challenges requires strong analytical skills, familiarity with bioinformatics tools, and ongoing collaboration with genetic counselors, laboratory directors, and clinicians. Staying current through continuous education and attending case discussions or multidisciplinary meetings also helps analysts provide accurate and clinically relevant interpretations.

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

To thrive as a Clinical Variant Analyst, you need a strong background in genetics, molecular biology, and bioinformatics, typically supported by a relevant degree such as in genetics or molecular biology. Familiarity with next-generation sequencing (NGS) platforms, variant interpretation databases (like ClinVar), and clinical reporting software is commonly required, along with certifications such as ACMG variant interpretation training. Attention to detail, analytical thinking, and effective communication are vital soft skills for accurately interpreting genetic data and collaborating with clinical teams. These skills ensure accurate variant classification and reporting, directly impacting patient diagnosis and care.
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Clinical Variant Analyst jobs near you
Senior Data Scientist, Bioinformatics

Senior Data Scientist, Bioinformatics

Precigen, Inc

Germantown, MD • On-site

$85K - $120K/yr

Full-time

Posted 14 days ago

Job description

GENERAL DESCRIPTION:

We are seeking a proficient Senior Data Scientist within Precigen’s Bioinformatics team who will be responsible for sequence data analysis, statistical analysis, and data mining. This individual will maintain and develop analysis pipelines, run data analyses, visualize results and communicate them to lab scientists and principal investigators. Extensive experience with DNA and RNA sequencing analysis and strong knowledge of statistical methods, coupled with a solid understanding of foundational biological principles, will be required. You will join a transnational team working at the intersection of biology, data science, and software development.

DUTIES AND RESPONSIBILITIES:

  • Perform computational analysis of DNA and RNA sequences.
  • Perform statistical analyses on experimental data from molecular and cell biology, immunology and oncology.
  • Mine clinical data with machine learning methods.
  • Perform computational analysis of protein sequence data.
  • Visualize and communicate analysis results to biologists.
  • Contribute to scientific writing.


EDUCATION AND EXPERIENCE:

  • PhD, MS, or equivalent experience in molecular biology, biochemistry, computational biology, bioinformatics or a related discipline.
  • Five or more years of experience with computational DNA analysis (insertion analysis, variant analysis), bulk and single cell RNA analysis, expression analysis, and pathway analysis.
  • Familiarity with bioinformatics concepts and standard tools for sequence data handling, sequence alignment, and differential expression analysis.
  • Good knowledge of statistics.
  • Familiarity with the Unix/Linux command line.
  • Strong programming skills in R and Perl.
  • Extensive experience with data analysis and visualization.
  • Knowledge of and experience with machine learning concepts and methods.
  • Experience with protein sequence analysis from mass spectrometry data.
  • Familiarity with AI-based tools is appreciated.

DESIRED KEY COMPETENCIES:

  • Capable of adapting to rapidly changing and developing requirements.
  • The candidate can engage effectively with scientists to understand the design, rationale, and scientific context of lab experiments, ensuring that data analyses align with experimental goals.
  • They can clearly communicate the methods, reasoning, results, and interpretations of their analyses within the Bioinformatics team and across research groups.
  • Ready to seek, accept, and provide feedback and advice from and to team colleagues and management.
  • Communicates issues and problems openly and early.
  • Exhibits high performance both independently and in a team setting.
  • Delivers work on schedule and within agreed timeframes.
  • Is comfortable with communicating predominantly via electronic means.
  • Effectively conveys information in a clear, structured manner.
  • Can interact proficiently in an international and culturally diverse environment where not everyone is a native speaker of English.
  • Sufficient language skills in German to discuss professional matters are a plus.


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