1

Biological Data Science Internship Jobs (NOW HIRING)

Scientist, Data Science

Waltham, MA ยท On-site

$91K - $136K/yr

D. in Bioinformatics, Computational Biology, Data Science, Epidemiology, or a related field (0-2 ... Prior experience or internship in the pharmaceutical or biotechnology industry. * Prior experience ...

Scientist, Data Science

Waltham, MA ยท On-site

$91K - $136K/yr

D. in Bioinformatics, Computational Biology, Data Science, Epidemiology, or a related field (0-2 ... Prior experience or internship in the pharmaceutical or biotechnology industry. * Prior experience ...

... diverse biological data can answer challenging scientific questions, generate therapeutic ... A decentralized model that enables our program teams to focus on advancing science and helping ...

Whether you come from a deep biological background with strong computational skills or a data science background with a proven track record in working with biological data, you will play a critical ...

Data Science Associate (Governance) Company Overview At Mitsubishi Power, we're not just building better clean energy technologies; we're architecting a better future. Our team is boldly redefining ...

You'll work at the intersection of computational biology, machine learning, and drug development ... Lead and execute complex data science projects that directly advance our drug development portfolio

Showing results 21-40

Biological Data Science Internship information

See salary details

$9

$17

$23

How much do biological data science internship jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for biological data science internship in the United States is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $19.23 per hour, depending on experience, location, and employer.

What is a biological data science internship?

A Biological Data Science Internship is a temporary position for students or recent graduates to gain practical experience working at the intersection of biology and data science. Interns typically analyze biological datasets using computational tools, statistical methods, and programming languages such as Python or R. They may work on projects involving genomics, bioinformatics, drug discovery, or ecological modeling. The internship helps individuals develop both technical and domain-specific skills, preparing them for future careers in research, biotechnology, or academia.

What types of projects do interns typically work on during a biological data science internship?

Biological Data Science interns often work on projects involving the analysis of large biological datasets, such as genomic, proteomic, or clinical data. Typical tasks may include cleaning and preprocessing data, developing statistical models, and visualizing complex biological patterns. Interns frequently collaborate with both data scientists and biologists, gaining exposure to interdisciplinary teamwork and real-world research challenges. This hands-on experience helps interns build both their technical and scientific communication skills, making it a valuable stepping stone for careers in bioinformatics, computational biology, or related fields.

What are the key skills and qualifications needed to thrive as a biological data science intern, and why are they important?

To thrive as a Biological Data Science Intern, you need a solid background in biology, statistics, and programming, often supported by coursework or a degree in bioinformatics or a related field. Familiarity with tools like Python, R, and data analysis platforms, as well as experience with genomic databases and visualization software, is typically expected. Strong problem-solving, attention to detail, and teamwork skills help interns excel in collaborative research environments. These abilities enable accurate analysis of complex biological data and contribute to meaningful scientific discoveries.

What is the difference between Biological Data Science Internship vs Biological Data Analyst?

AspectBiological Data Science InternshipBiological Data Analyst
Required CredentialsUndergraduate or graduate student in biology, data science, or related fieldBachelor's or master's in biology, data science, or related field; sometimes requires experience
Work EnvironmentResearch labs, biotech companies, academic institutions, often temporary or project-basedCorporate or research settings, ongoing role with regular hours
Employer & Industry UsageInternships offered by biotech firms, research institutions, universitiesFull-time roles in biotech, pharmaceuticals, research organizations

The Biological Data Science Internship is typically a temporary, entry-level position aimed at students gaining practical experience, whereas a Biological Data Analyst is a full-time role requiring more experience and responsibility. Internships focus on learning and skill development, while analysts handle ongoing data analysis tasks in professional settings.

More about Biological Data Science Internship jobs

What cities are hiring for Biological Data Science Internship jobs?

Cities with the most Biological Data Science Internship job openings:

What states have the most Biological Data Science Internship jobs?

States with the most job openings for Biological Data Science Internship jobs include:

Infographic showing various Biological Data Science Internship job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $35,995 per year, or $17.3 per hour.

Scientist/Sr. Scientist, Bioinformatics Data

Legend Biotech US

Somerset, NJ โ€ข Hybrid

Full-time

Re-posted 19 days ago


Job description

Legend Biotech is seeking a Scientist/Sr. Scientist, Bioinformatics Data as part of the Early Drug Development team based in Somerset, NJ.

Role Overview

We are seeking a highly motivated, passionate, and driven Bioinformatics Data Scientist with high scientific curiosity to join our research and development team. In this role, you will bridge the gap between complex biological datasets and actionable therapeutic insights. You will design, develop, and execute scalable computational pipelines to analyze high-dimensional genomic data.The ideal candidate possesses a deep curiosity for biological systems, an analytical mindset, and the technical skillset to tackle unstructured, diverse and complex multiomics challenges. Whether you come from a deep biological background with strong computational skills or a data science background with a proven track record in working with biological data, you will play a critical role in accelerating both our discovery and clinical pipeline.

Key Responsibilitiesย 

  • Analyze diverse and large-scale genomic datasets (e.g., RNA-seq, scRNA-seq, WES/WGS, epigenetic, or multi-omics data) to identify biomarkers, therapeutic targets, or disease mechanisms.
  • Apply advanced statistical, machine learning, and data-mining techniques to extract meaningful patterns from noisy biological data.
  • Perform quality control, normalization, and batch-correction across heterogeneous datasets.
  • Design, optimize, and maintain robust, scalable bioinformatics pipelines.
  • Implement version-controlled code architectures to ensure reproducibility and scalability of data analyses.
  • Procure and integrate existing biological databases with internal datasets.
  • Translate complex computational and statistical findings into clear biological narratives for experimental biologists, clinicians, and stakeholders.
  • Collaborate with IT and other functional groups.

Requirements

  • Ph.D. or M.S. in Bioinformatics, Computational Biology, Data Science, Genomics, Biology, or a highly quantitative field.
  • Proven experience handling genomic data (Next-Generation Sequencing/NGS data analysis is required).
  • Ability to turn raw biological data into structured insights.
  • Strong experience with AI application in data science.
  • Advanced proficiency in R (e.g., Bioconductor, Tidyverse) and/or Python (e.g., Pandas, NumPy, Scikit-learn).
  • Experience with standard bioinformatics tools (e.g., alignment tools, variant callers, single-cell toolkits like Seurat/Scanpy).
  • Experience with cloud computing platforms (AWS, GCP) and containerization (Docker, Singularity) is a strong plus.
  • A self-starting attitude with an intrinsic desire to stay ahead of the curve in emerging computational methods and biological technologies.
  • Proven ability to thrive in a fast-paced environment, manage multiple projects simultaneously, and pivot quickly based on data-driven feedback.
  • Exceptional critical thinking skills with a knack for debugging complex code and parsing unstructured data formats.
  • Creative, innovative and excellent communication and presentation skills.
  • This role is designed as the starting point of group effort to solve complex biological and clinical problems in a fast paced environment. We look for individuals who take extreme ownership of their expertise and training, and driven by the prospect of turning data into information, and information into knowledge.

#Li-JR1

#Li-Hybrid