Data Science Intern

Data Science Intern — Epoetic

Paid internship · ~£15/hour · part-time (~15 hrs/week, flexible around study) · Falmouth or Bristol (hybrid / remote-friendly) · clear route to permanent

About us

Epoetic is a small, founder-led data and analytics company working at the sharp end of environmental sensing. We turn messy real-world data from emissions-detection and methane-survey programmes — vehicle fleets, sensors and geospatial networks — into tooling, automation and analytics that help find and fix gas leaks across the country. It's genuinely useful work: better data means faster leak detection, lower emissions and safer networks. We're also developing our own next-generation environmental sensing technology.

We're growing, and this is a paid internship with a real path to a permanent role for the right person. You won't be making coffee or watching from the sidelines — you'll do real work that ships, mentored directly by the founder (first-class Computer Science / AI background, ongoing PhD research in optimisation).

Where you'll start

Whatever the role, everyone starts by getting fluent in our day-to-day operational flow. It's how you learn the data, the domain and the tools properly:

• QA — checking and validating data and outputs so everything we deliver is trustworthy
• Data analysis — turning raw survey and operational data into clear answers
• GIS data annotation — working with geospatial network data: labelling, tidying, reconciling
• Running automation pipelines — operating (and gradually improving) the automated processes that keep everything moving

Once you know how the engine runs, you specialise.

Where you'll grow (the data science side)

• Building trustworthy metrics and KPIs from operational and survey data
• Statistical analysis, performance and productivity insight, anomaly spotting
• Turning analysis into clear, honest reporting and visualisations stakeholders actually use
• Growing toward the harder problems we work on: forecasting, route and resource optimisation, applied ML

What we work with

• Python — pandas, NumPy, scikit-learn
• Jupyter notebooks
• Data visualisation — matplotlib, Plotly
• geopandas and geospatial analysis
• SQL
• Nice to have: exposure to optimisation (OR-Tools), basic ML, QGIS/ArcGIS

You might be a good fit if you

• Are studying, or have recently finished, a numerate degree (Data Science, Computer Science, Maths, Physics, or similar)
• Are comfortable in Python and genuinely enjoy getting your hands into real-world data
• Are curious and rigorous — you care whether a number is actually right
• Can explain what you found to someone who isn't a data scientist

You don't need to tick every box. Enthusiasm, honesty and a good head for problems matter more than a perfect CV.

To apply

• Send a CV and a couple of lines on why this interests you — plus a link to anything you've built (GitHub, a project, a notebook) if you have it — to theo@epoetic