Biotech Data Scientist Internship information
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$81.9K - $99.9K
4% of jobs
$99.9K - $117.8K
9% of jobs
$133.1K is the 25th percentile. Wages below this are outliers.
$117.8K - $135.8K
11% of jobs
$135.8K - $153.7K
7% of jobs
The median wage is $159.5K / yr.
$153.7K - $171.7K
50% of jobs
$171.7K - $189.6K
2% of jobs
$189.6K - $207.6K
1% of jobs
$207.6K - $225.5K
0% of jobs
$225.5K - $243.5K
13% of jobs
How much do biotech data scientist internship jobs pay per year?
As of Aug 29, 2026, the average yearly pay for biotech data scientist internship in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.
A Biotech Data Scientist Internship is a temporary position where students or recent graduates work at the intersection of biotechnology and data science. Interns typically analyze large biological datasets, apply machine learning techniques, and help interpret experimental results to support research and development in biotech companies. This internship provides hands-on experience with bioinformatics tools, data visualization, and statistical analysis. It is designed to help interns develop practical skills, gain industry exposure, and contribute to real-world biotech projects.
Biotech Data Scientist Interns often work with a variety of biological and clinical data sets, including genomic, proteomic, and experimental data. Projects may involve analyzing large-scale sequencing data, building predictive models for drug discovery, or developing algorithms to interpret laboratory results. Interns usually collaborate closely with bioinformaticians, wet-lab scientists, and software engineers, gaining hands-on experience with data cleaning, visualization, and statistical analysis. This exposure not only sharpens technical skills but also provides valuable insight into real-world biotech research workflows.
To thrive as a Biotech Data Scientist Intern, you need a solid understanding of statistics, biology, and data analysis, often supported by coursework or a degree in bioinformatics, computer science, or a related field. Familiarity with programming languages like Python or R, experience with data visualization tools, and knowledge of bioinformatics databases and pipelines are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help set top candidates apart. These skills and qualities ensure meaningful data insights, accurate research results, and clear collaboration across multidisciplinary teams in the biotech field.
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