Data Operations Intern (Summer 2027)

The Role

You'll join the Data Operations team, the group that turns raw street-level capture into the map layers 500+ cities rely on. Every day, sensor data from the field flows through our processing pipelines and comes out as road conditions, sidewalk inventories, sign catalogs, and pavement scores. You'll own pieces of that pipeline: running deliveries end to end, catching data problems before a customer does, and writing the scripts that make the next delivery faster than the last.

What You'll Do

• Process customer deliveries end to end: run geospatial data through our Python pipelines, validate the output, and publish the final layers to the Cyvl platform.
• Build QC checks that review data automatically.
• Investigate failed and stalled processing jobs in our AWS pipelines, find the root cause, and document the fix.
• Automate recurring manual steps into repeatable scripts and runbooks, and measure the time saved.
• Partner with engineering and customer success to turn field-reported issues into code fixes or process improvements.

What You Bring

• Currently pursuing a degree in Computer Science, Data Science, or a related field
• Proficiency in Python; comfortable writing scripts that read, transform, and validate data
• Comfort working in a terminal and with version control
• Available full-time for 10-12 weeks in Summer 2027, based in our Somerville office

Nice to Have

• GIS experience (QGIS or ArcGIS, and formats like GeoJSON, shapefiles, GeoPackage)
• Familiarity with cloud infrastructure, especially AWS
• SQL and experience querying real datasets
• Exposure to geospatial Python libraries (geopandas, shapely)
• Interest in civic infrastructure, transportation, or public-sector technology
• A knack for the business side: you think about how data drives decisions and like problems like "how do we track this better" or "how do we make this visible to the team"
• Experience building dashboards or turning data into something a non-technical person can act on

Why Cyvl

• Hard tech.
• Real streets.
• Your name on it.

• Hard problems in the real world. You build end-to-end: our own hardware, software and AI, with work that shows up on the street in the real world.
• Ownership that compounds. You own outcomes, not tasks. You work directly with customers and across our team, and you'll own more, sooner, than almost anywhere else.
• Intense, with heart. We're building a category, so it's not a place to coast. We also take care of each other, have genuine fun together, and believe in what we are doing.

What We Ask

• Cross lanes. "Not my job" doesn't exist here.
• Own without a playbook. The plan is still being written, often by you.
• Try, miss, try again. We make big bets. Some won't land, and we learn fast.
• Be in the room. We're on-site in Somerville about 90% of the time.

We're a startup building a category. If that sounds like the draw, not the risk, we'd love to talk.

See Our Work

• How Atlanta cut downtown potholes by 60%
• How Buffalo turned a campaign promise into a paving plan
• How to rebuild US infrastructure smarter

Want to Go the Extra Mile? (Optional)

If you're excited about this role and want to tell us more, email with the subject line "Data Ops Intern, [Your Name]" and answer any or all of these:

• Why Cyvl, and why a startup? What draws you to this kind of work, and to a small team where your work ships right away?
• What's the coolest thing you've built with AI? A class project, side project, script, or experiment all count. Tell us what it did and what you learned.
• Tell us about a time you solved a problem by fixing the process instead of just working harder. What was slowing you down? What did you change? What happened?

A few honest paragraphs beat an AI-slop essay. Links to code, notebooks, or demos are welcome.

We build for every community, so we hire from all of them. The best people for this work come from different backgrounds, paths, and places, and many of them don't check every box. If this role excites you, apply anyway. If you need an adjustment to our interview process, tell us and we'll make it work.