At a Glance
- Tasks: Help build a digital twin of UK flats and analyse building risk data.
- Company: Exciting early-stage company with a focus on innovation.
- Benefits: Equity options, direct impact on pricing, and fast learning opportunities.
- Other info: Opportunity for full-time role after initial three months.
- Why this job: Shape core company assets and make a real difference from day one.
- Qualifications: Degree in a quantitative field and programming skills, ideally Python.
The predicted salary is between 28000 - 35000 £ per year.
We're looking for a graduate data scientist to help build and exploit a digital twin of every block of flats in the UK — a single, structured, continuously updated model of the buildings we insure and the ones we might. You'll do two things:
- Help build the data foundation: bringing together public and commercial datasets and resolving them to individual buildings.
- Use that data to understand the true risk of each building and turn it into pricing, risk selection and insight we give back to clients.
Initially, this is a three month role with the potential to become full time. This is a rare chance to own foundational work from day one at an early-stage company, with real scope to shape both the data and the models built on it.
What you'll do:
- Help build and maintain the digital twin — ingesting, cleaning, matching and enriching building-level data from multiple sources.
- Work with UK datasets including Ordnance Survey (e.g. AddressBase, building footprints), Land Registry, EPC records, planning data, flood and other peril data, and commercial sources.
- Solve entity resolution — reliably matching records across datasets to the right physical building and address.
- Analyse and model risk at building level — identifying the features that actually drive claims and turning them into signals for pricing and underwriting.
- Build, test and validate models, and clearly communicate what they do and don't tell us.
- Work with large databases and keep them accurate and performant as they grow.
- Help define what 'good' looks like — data quality, coverage, model performance — and build the checks to enforce it.
Why join:
- Real ownership — you'll shape a core company asset and the models built on it, not maintain someone else's legacy system.
- Equity — share in what we're building.
- Direct impact — your work shapes how we price risk and what we tell clients.
- Learn fast — work directly with the founder and a small, senior team.
Essential:
- A degree in a quantitative subject (e.g. data science, statistics, maths, physics, engineering, computer science, economics, geography/GIS) — or equivalent demonstrable skill.
- Strong analytical and statistical reasoning, and sound judgement about data.
- Programming ability, ideally Python; comfortable with SQL and large datasets.
- Genuine interest in working with messy real-world data and making it reliable and useful.
- Clear thinker who can break down ambiguous problems and take ownership.
Nice to have:
- Experience building statistical or machine-learning models on real data.
- Hands‑on experience with Ordnance Survey data or other UK public datasets.
- Geospatial / GIS experience (e.g. PostGIS, QGIS, working with coordinates and footprints).
- Any exposure to property, insurance, actuarial work, or the built environment.
You don't need to tick every box. If you're a sharp graduate who loves data and wants to build something foundational, we want to hear from you.
Data Scientist employer: Tussell Limited
Join a pioneering early-stage company where you will have the unique opportunity to take ownership of foundational work in building a digital twin of UK flats. With a strong emphasis on real impact, equity sharing, and direct collaboration with senior leadership, this role offers an enriching work culture that fosters rapid learning and professional growth. You'll be at the forefront of shaping data models that influence pricing and risk assessment, making your contributions vital to our mission.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Tussell Limited will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at Tussell Limited
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Tussell Limited.
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Tussell Limited that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
