At a Glance
- Tasks: Work with AI tools to clean data and validate outputs for clients.
- Company: Join a fast-paced startup revolutionising financial data extraction.
- Benefits: Competitive pay, hands-on experience, and potential for full-time role.
- Other info: Dynamic team environment with opportunities for rapid learning and growth.
- Why this job: Gain real responsibility and learn how to build AI agents from day one.
- Qualifications: Fluency in Python and experience with data analysis required.
The predicted salary is between 3000 - 5000 £ per month.
Arctal builds structured datasets from unstructured financial documents—100,000+ PDFs (fund reports, regulatory filings, investor letters) turned into clean, queryable data that institutional buyers use for decision-making. AI agents do the reading. We build the agents. Team of 5, output of 50.
A dataset is not a fact. It's a representation of reality that someone chose to stand behind. AI agents do the extraction—humans make the judgement calls. You'll learn what that means in practice.
Our customers are asset managers, banks, and financial data firms who need reliable data extracted from documents that were never meant to be machine-readable.
The role
- You’ll work with the Data Scientist and technical team to deliver datasets to clients. This is your introduction to the super-IC model—learning what it means to direct agents rather than do the work yourself.
- Data Quality. Validate data outputs, catch errors, and flag issues before data goes to clients. You're the human-in-the-loop that makes sure quality is high. You'll develop an eye for what great data looks like—and what's subtly wrong.
- Agent-Led Data Work. Use Claude Code, Cursor, and other AI tools to process documents, clean data, and build small automations. You'll spend a lot of time in the terminal, in Python, and in messy datasets—and that's the point. The technical team will help you level up.
- Process Improvement. Spot patterns in what's slow or broken. Suggest fixes. If you find a better way to do something, we'll use it. At Arctal, every person is building themselves out of their current role—automating the task they did yesterday so they can take on the harder problem tomorrow.
This is a hands‑on role. You'll have real responsibility from day one—not coffee runs and slide decks.
You
- Final-year student, master's student, or early-career—what matters is what you can do, not your CV.
- Data-obsessed. You've spent real time working with data—cleaning it, analyzing it, understanding why it's wrong. You know the difference between data that looks right and data that is right. You notice when numbers don't add up.
- Technically deep. You're fluent in Python and comfortable in the terminal. You've written scripts, built pipelines, or wrangled messy datasets. You don't need hand-holding on technical work.
- AI-native (for real). You actively use AI coding tools—Cursor, Claude Code, Windsurf, Cline, or similar. You know the difference between chat-based AI and agentic coding. Your first instinct facing a new problem is to design a system that solves it autonomously. You've probably broken something by letting Claude run too many commands unsupervised.
What we're filtering for. We need someone who is technical and data-first. Previous hires that didn't work out were people who weren't deep enough in data or weren't fluent with AI coding tools. If you haven't spent significant time in the terminal, in codebases, and in messy datasets, this isn't the right role.
What matters: curiosity, attention to detail, bias to action. You care about getting things right, not just getting things done. You see AI agents as leverage, not a threat—and you're excited to be the one building them, not the one being replaced by them.
What this isn't
- An assistant role (you’ll own real deliverables)
- A learning-only experience (you’ll ship to real clients)
- A 9-to-5 (intensity is high, learning is faster)
Founders
- Aleksi (CEO) — Cambridge engineering + ML. Co-founded Secondmind, founding team at Sylvera. Previously worked on ML with Carl Rasmussen at Cambridge.
- Krista (CCO) — Former Head of Market Intelligence at Climate Bonds Initiative. Deep sustainable finance and capital markets expertise.
Small team that ships fast. No layers, no politics—just building.
What you get
- Old Street office.
- Real work with real clients from week one.
- Freedom to use AI tools however you want.
- A team that will teach you how startups actually work.
- For strong performers, this converts to a full-time Data Scientist role managing your own fleet of agents.
Data Scientist Intern, AI Agents Filled Internship · London · ~3 months · £3k–5k monthly employer: Arct a L
Arctal is an exceptional employer for aspiring data scientists, offering a dynamic work environment in the heart of London. With a focus on hands-on experience and real responsibility from day one, interns will engage directly with clients and have the opportunity to leverage cutting-edge AI tools while receiving mentorship from a small, agile team. The company fosters a culture of innovation and continuous improvement, ensuring that every team member can grow and evolve their role, making it an ideal place for those passionate about data and technology.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist Intern, AI Agents Filled Internship · London · ~3 months · £3k–5k monthly
✨Tip Number 1
Get your hands dirty with data! Dive into messy datasets and start playing around with Python. The more you experiment, the better you'll understand what makes data tick, which is exactly what Arctal is looking for.
✨Tip Number 2
Show off your AI skills! If you've been using tools like Claude Code or Cursor, make sure to highlight that in conversations. We want to see how you can leverage these tools to solve real problems, so be ready to share examples.
✨Tip Number 3
Be proactive about process improvement. If you spot something that's slow or broken, don’t just sit on it—bring it up! At Arctal, we love fresh ideas, and showing that you can think critically about workflows will set you apart.
✨Tip Number 4
Apply through our website! It’s the best way to get noticed. Make sure to tailor your application to show how your skills align with what we do at Arctal. We’re excited to see what you can bring to the team!
We think you need these skills to ace Data Scientist Intern, AI Agents Filled Internship · London · ~3 months · £3k–5k monthly
Some tips for your application 🫡
Show Your Data Passion:Let us see your love for data shine through! Share specific examples of how you've worked with data, cleaned it, or even spotted errors. We want to know what makes you tick when it comes to data.
Be Technical and Specific:We’re looking for someone who’s fluent in Python and comfortable in the terminal. Don’t just say you can code—give us details about projects you've worked on, scripts you've written, or datasets you've wrangled. Show us your technical chops!
Highlight Your AI Experience:If you’ve used AI coding tools like Claude Code or Cursor, make sure to mention it! We want to know how you’ve leveraged these tools in your work. Tell us about a time you designed a system that solved a problem autonomously.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to see your application in the right context. Plus, it shows us you’re serious about joining our team at Arctal!
How to prepare for a job interview at Arct a L
✨Know Your Data
Before the interview, brush up on your data skills. Be ready to discuss your experience with cleaning and analysing datasets. Highlight specific examples where you identified errors or improved data quality—this will show your attention to detail and data obsession.
✨Show Off Your Technical Skills
Make sure you're comfortable discussing Python and any AI coding tools you've used. Prepare to talk about scripts you've written or pipelines you've built. If you can, bring along a portfolio of your work or examples of projects that demonstrate your technical depth.
✨Demonstrate Curiosity and Problem-Solving
Arctal values curiosity and a bias to action. Think of instances where you spotted inefficiencies in processes and suggested improvements. Be ready to discuss how you approach problem-solving, especially when it comes to using AI tools to automate tasks.
✨Understand the Role and Company Culture
Familiarise yourself with Arctal's mission and the specifics of the Data Scientist Intern role. Show that you understand the importance of being the 'human-in-the-loop' and how you can contribute to the team from day one. This will demonstrate your genuine interest in the position.
