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EEnveda

Data Science Intern

United StatesListed 11h ago

  • Remote
  • Internship
  • MS
  • PhD

About this role

Let’s build the future of medicine - together.
Remote (US or Canada) | Internship
Compensation per month: US - Masters ($5000 USD), PhD ($6000 USD) & Canada - Masters or PhD ($8500 CAD) 
YOUR ROLE
As a Data Science Intern at Enveda, you will join our Data Science team and work on machine learning for mass spectrometry, computational biology, and computational chemistry. You will own a project from scientific question to result. Your work will inform how we apply AI and data science to drug discovery, and you will work with some of the strongest scientists in the field. Here are some example projects from last year’s interns: [1],[2], [3], [4], [5].

WHAT YOU'LL DO

- Learn how to develop data-driven solutions tailored to the drug discovery industry as part of our Data Science team

- Collaborate on machine learning for mass spectrometry

- Collaborate on computational biology and computational chemistry

WHAT WE'RE LOOKING FOR

- Strong scientific reasoning and research skills, shown through publications, preprints, a thesis, or projects

- Familiarity with LLMs and coding agents, including tool use and multi-step reasoning, and experience using them to build analyses (Claude Code, Cursor, or similar)

- Ability to write clear task specifications and to validate AI output with tests, sanity checks, and controls

- Python for data analysis, including the ability to read, debug, and review code written by an AI tool

- Solid grasp of statistics, probability, and machine learning

- Ability to present scientific results clearly and quickly, through data visualization and in writing

- Experience with metabolomics data, from LC-MS or NMR

- Based in the US or Canada

- Currently enrolled in a PhD program (strongly preferred)

We hire for trajectory, not just credentials. If you meet most of the above and care deeply about this problem, we want to hear from you. 
ABOUT ENVEDA
We're a clinical-stage, AI-enabled biotech discovering medicines from nature four times faster than the industry standard. We recently raised $311M in a Series E, bringing total funding to over $845M, and doubled our valuation to $2B. We now have three oral medicines in the clinic, including our lead drug, ENV-294, in Phase 2 trials for eczema and asthma. Forbes named us one of America's Best Startup Employers, and Newsweek recognized us as a Top 100 Most Loved Workplace. We're still early, and most of the best work is ahead of us.
Benefits: Work-Life Harmony | Collaborative Culture 
Our Process: We move fast and respect your time. Typically: a recruiter screen → hiring manager conversation → work sample, technical interview, & culture interview.
Our Values: Curiosity | Agency | Journey | Charity | Unity
---------------------
Enveda is protecting Job Seekers
We care deeply about creating a safe, respectful experience for every applicant, so we wanted to share a few guidelines to help you spot anything that doesn’t feel right.
You’ll always meet real Enveda team members through video or in-person conversations before receiving an offer.
All communication from us will come from an @enveda.com or @envedabio.com email address.
We’ll never ask you to purchase equipment, send money, or share sensitive banking details as part of any step in our recruiting process.
If something feels off or you’re unsure whether a message is truly from Enveda, please reach out at anytime at recruiting@enveda.com.

At Enveda, we’re building a place where everyone can do the best work of their life. We are an equal opportunity employer and value diversity in all its forms. Apply now and join a team committed to shaping the future of drug discovery.

$5,000/moListed pay
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Location
United States
Work model
Remote
Role type
Internship
Degrees
MS · PhD
Family
Data Science
Listed
11h · Nov 10, 2026
E

Enveda

Series D · 201–500 employees

  • Biotech & Pharma
  • AI & Machine Learning
  • Healthcare & Health Tech

Enveda is a biotechnology company that uses machine learning, metabolomics, and automated laboratories to discover small-molecule medicines from nature’s chemistry for complex diseases.

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