Internship Genomic Data Analyst Jobs in Remote, OR

As of Aug 13, 2026, the average hourly pay for internship genomic data analyst in Remote, OR is $22.48, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.47 per hour, depending on experience, location, and employer.

To thrive as an Internship Genomic Data Analyst, you need a foundational knowledge of genetics, statistics, and bioinformatics, usually supported by coursework in biology, computational sciences, or related fields. Familiarity with programming languages such as Python or R, experience with genomic databases, and basic proficiency in data analysis tools are commonly required. Strong analytical thinking, attention to detail, and effective teamwork skills help interns excel in collaborative research environments. These competencies are crucial for accurately interpreting complex genomic data and contributing meaningful insights to scientific projects.

An Internship Genomic Data Analyst is a trainee or student who assists with analyzing and interpreting large sets of genetic data, often as part of a research or healthcare team. They typically use bioinformatics tools and programming languages to process DNA, RNA, or protein sequences, identify genetic variants, and generate reports. The internship provides practical experience working with genomic datasets, familiarizing interns with industry-standard analysis methods and laboratory workflows. This role is ideal for students in biology, bioinformatics, or computer science looking to gain hands-on experience in genomics. Responsibilities may include data cleaning, statistical analysis, and collaborating with scientists to draw meaningful conclusions from genetic data.

As an Internship Genomic Data Analyst, you will likely work on tasks such as cleaning and preprocessing genomic datasets, running bioinformatics pipelines, and performing statistical analyses to interpret genetic data. Your day-to-day responsibilities may also include data visualization, assisting with literature reviews, and collaborating closely with both computational and biological researchers. Interns often gain exposure to a variety of genomic technologies and analytical tools, providing practical experience that helps build a strong foundation for future roles in the field.