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Internship Biomedical Data Scientist Jobs (NOW HIRING)

Ceribell, Inc

Senior/Staff Data Scientist

Sunnyvale, CA · On-site

We are looking for a talented data scientist/algorithm engineer who is passionate about biomedical ... Mentor and guide junior data scientists and interns, fostering their growth by providing technical ...

MIT Lincoln Laboratory

Data Scientist

Lexington, MA · On-site

Master's in Data Science, Computational Biology, Biomedical Informatics, AI, or related scientific field or equivalent experience in technical analysis. In lieu of a Master's degree, a bachelor ...

MIT Lincoln Laboratory

Data Scientist

Lexington, MA · On-site

Master's in Data Science, Computational Biology, Biomedical Informatics, AI, or related scientific field or equivalent experience in technical analysis. In lieu of a Master's degree, a bachelor ...

MIT Lincoln Laboratory

Data Scientist

Lexington, MA · On-site

Master's in Data Science, Computational Biology, Biomedical Informatics, AI, or related scientific field or equivalent experience in technical analysis. In lieu of a Master's degree, a bachelor ...

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Internship Biomedical Data Scientist information

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$37.5K

$122.7K

$196.5K

How much do internship biomedical data scientist jobs pay per year?

As of Sep 10, 2026, the average yearly pay for internship biomedical data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What does an internship biomedical data scientist do?

An Internship Biomedical Data Scientist assists in collecting, analyzing, and interpreting large sets of biomedical data to support research and healthcare innovation. Interns typically work with interdisciplinary teams to process data from sources such as clinical trials, electronic health records, or genomics studies. They use statistical methods and programming tools to uncover patterns, test hypotheses, and help develop predictive models that can improve patient outcomes or advance medical research.

What are the key skills and qualifications needed to thrive as an internship biomedical data scientist?

To thrive as an Internship Biomedical Data Scientist, you typically need a strong background in statistics, programming (such as Python or R), and a foundational understanding of biology or medicine, often supported by progress toward a relevant degree. Familiarity with data analysis tools, machine learning libraries, and bioinformatics platforms like TensorFlow, scikit-learn, and databases such as SQL is important. Effective communication, problem-solving abilities, and teamwork help interns interpret results and collaborate with interdisciplinary teams. These skills enable accurate data-driven insights and successful contributions to biomedical research and innovation.

What types of projects can an internship biomedical data scientist expect to work on?

As an Internship Biomedical Data Scientist, you can expect to work on projects involving data cleaning, statistical analysis, or machine learning model development using large biomedical datasets such as genomics, clinical trial data, or electronic health records. These projects often support ongoing research by identifying meaningful patterns or developing predictive models that inform clinical decisions or product innovation. You'll typically collaborate with multidisciplinary teams, including biologists, clinicians, and software engineers, which provides valuable exposure to real-world biomedical challenges and workflows. This hands-on experience is instrumental for understanding how data science drives progress in healthcare and biotechnology.

What is the difference between Internship Biomedical Data Scientist vs Biomedical Data Scientist?

AspectInternship Biomedical Data ScientistBiomedical Data Scientist
Required CredentialsEnrolled in or recent graduate of relevant degree (e.g., bioinformatics, data science)Bachelor's or higher in related field, often with experience or certifications
Work EnvironmentInternship programs, research labs, healthcare companiesFull-time roles in research institutions, biotech, healthcare firms
Employer & Industry UsageEducational institutions, hospitals, biotech startupsEstablished companies, research organizations, pharma
Search & Comparison IntentLearning about entry-level opportunities, internshipsSeeking full-time roles, career advancement

The main difference is that an Internship Biomedical Data Scientist is an entry-level, temporary position aimed at gaining experience, while a Biomedical Data Scientist is a full-time professional role requiring more experience and qualifications. Internships serve as a stepping stone toward a full career in biomedical data science.

What cities are hiring for Internship Biomedical Data Scientist jobs?

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What are the most commonly searched types of Biomedical Data Scientist jobs?

The most popular types of Biomedical Data Scientist jobs are:

What states have the most Internship Biomedical Data Scientist jobs?

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For Internship Biomedical Data Scientist jobs, the most frequently searched job titles are:

Internship Biomedical Data Scientist jobs near you

Bioinformatics Data Scientist (Part-time/Temporary)

San Diego, CA • On-site

Artiva Biotherapeutics Inc.
Biotechnology Research and Development • 11 - 50 employees
Learn more about Artiva Biotherapeutics Inc.external

$55 - $65/hr

Other

Posted 20 days ago

Job description

About Artiva:

We are a clinical-stage biotechnology company focused on developing natural killer (NK) cell-based therapies. Our mission is to develop effective, safe, and accessible cell therapies for patients with devastating autoimmune diseases. We aim to develop therapies that patients and physicians can utilize in a community setting. Our lead product candidate, AlloNK, is a non-genetically modified, cryopreserved NK cell therapy being evaluated in combination with B-cell targeted monoclonal antibodies (mAbs). We believe the compelling cell killing properties of NK cells, when combined with mAbs for targeting, creates an opportunity to generate potentially transformative therapies.

For more information, visit www.artivabio.com.

Position Summary:

Artiva Biotherapeutics is seeking a part-time/temporary Bioinformatics Data Scientist to help garner biological insights from multimodal biological data. You will design and maintain bioinformatics pipelines, generate insights, and build automated dashboards and reports in collaboration with wet-lab scientists, clinician-researchers, and data engineers.

Responsibilities:
  • Design, develop, and maintain bioinformatics pipelines and workflows for diverse biomedical data types including bulk RNA-seq, scRNA-seq, proteomic, and flow cytometric data.
  • Perform multi-omics and biomarker analysis including quality control, normalization, batch correction, differential expression analysis, clustering, dimensionality reduction (PCA, UMAP, t-SNE), cell type annotation, comparative analysis, and pathway analysis.
  • Support data integration, curation, and lifecycle management including annotation, data ingestion, metadata capture, schema management, and provenance tracking. Enable reliable data movement from source systems into structured, analysis-ready formats.
  • Build and support interactive dashboards, visualization tools, notebooks, and reports enabling researchers and clinicians to explore multi-omics, clinical, and sequencing data. Support figure generation for quality control, differential expression, and pathway analyses. Translate complex computational findings into clear biological narratives.
  • Collaborate with multidisciplinary teams including wet-lab scientists, bioinformaticians, clinician-researchers, biostatisticians, data engineers, and IT personnel.
Required Qualifications:
  • Bachelor’s or master’s degree (preferred) in Computer Science, Data Science, Bioinformatics, Computational Biology, or related field, and demonstrated experience (typically 2+ years) in bioinformatics pipeline development and biological data science.
  • Proficiency in Python for analysis, scripting, data science, and visualization. Familiarity with biological computing and data science libraries (e.g., Scanpy, Pandas, NumPy, scikit-learn).
  • In-depth knowledge of modern tools and pipelines for processing, aligning, and analyzing multimodal NGS and omics data. Knowledge of standard bioinformatics data formats (FASTQ, FCS) and related processing tools.
  • Proficiency with at least one pipeline framework (e.g., Airflow, Snakemake, Nextflow).
  • Experience with a cloud computing environment (GCP, AWS, Azure). Proficiency with queryable databases (e.g., PostgreSQL, BigQuery). Ability to work with structured, semi-structured, and unstructured data across relational and data lake environments.
  • Awareness of data governance, privacy, and compliance requirements for clinical and research data.
  • Strong background in constructing statistical models, hypothesis testing, regression analysis, clustering, and dimensionality reduction techniques. Demonstrated experience with machine learning (ML) methods and applying ML techniques to biological and clinical datasets. Knowledge of differential expression analysis, pathway analysis, and statistical methods relevant to genomic data.
Preferred Qualifications:
  • Advanced Development Tools: Experience with frameworks for web application development (Django, Flask, RShiny, Streamlit, React). Experience with CI/CD pipelines.
  • Advanced Biomedical Domain Knowledge: Background in biomedical research, clinical research, immunology, or healthcare analytics.
  • Governance & Data Management: Experience with metadata management, data lineage, open-source code release, containerized analyses, and secure handling of de-identified or access-controlled research datasets.
Compensation:

Compensation: $55 - 65/hr. Exact compensation may vary based on skills and experience.

If all this speaks to you, come join us on our journey!

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