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- Tasks: Transform unstructured financial data into clean, queryable datasets using AI agents.
- Company: Join Arctal, an innovative AI startup revolutionising financial data.
- Benefits: Competitive salary, equity options, and a dynamic work environment.
- Other info: Work with an elite team and gain exposure to top institutional clients.
- Why this job: Be at the forefront of AI technology and make a real impact in finance.
- Qualifications: 1-5 years experience in data science or analytics engineering with strong coding skills.
The predicted salary is between 60000 - 100000 £ per year.
Salary: £60–100k + Equity
Company Description: Arctal - AI startup building high-fidelity financial datasets
Location: London, UK
You will act as a super-IC managing a fleet of AI agents to transform 100,000+ unstructured financial PDFs into clean, queryable data for institutional buyers. This role sits at the intersection of data science and engineering, requiring you to design agentic workflows, prompt chains, and validation logic to ensure professional-grade accuracy at scale.
Why this role is remarkable:
- Work at the frontier of agentic workflows, using tools like Claude Code and Cursor to automate the extraction of complex data that was never meant to be machine-readable.
- Join an elite team of five with the output of fifty, founded by industry veterans from Secondmind and Sylvera with deep roots in Cambridge ML research.
- Enjoy high‑intensity growth and direct exposure to institutional customers like asset managers and banks, with meaningful equity in a fast‑shipping startup.
What you will do:
- Design and maintain agent‑led data pipelines using prompt chains and human‑in‑the‑loop checkpoints to ensure 100% data reliability.
- Build validation logic in Python and SQL that encodes your expert judgement to catch the edge cases and hallucinations AI agents might miss.
- Debug and optimize complex data ingestion and transformation systems, acting as the final line of defense before data reaches global financial clients.
The ideal candidate:
- Possesses 1–5 years of experience as a data scientist or analytics engineer with a track record of building production‑grade data pipelines, not just querying tables.
- Is an AI‑native practitioner who uses agentic coding tools like Cursor or Claude Code for real‑world engineering tasks rather than simple challenges.
Data Scientist, AI Agents ( + Equity) at Arctal employer: Jack & Jill/External Ats
Contact Detail:
Jack & Jill/External Ats Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist, AI Agents ( + Equity) at Arctal
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Arctal or similar startups. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and any projects using AI tools like Claude Code or Cursor. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss how you’ve tackled complex data challenges and how you’d approach the tasks at Arctal. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace Data Scientist, AI Agents ( + Equity) at Arctal
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Data Scientist, AI Agents. Highlight your experience with data pipelines and any tools like Python or SQL that you've used. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you're excited about working at Arctal and how you can contribute to our mission. Be genuine and let your personality come through – we love seeing the real you!
Showcase Relevant Projects: If you've worked on projects that involve AI, data transformation, or anything similar, make sure to mention them. We’re keen to see examples of your work that demonstrate your ability to handle complex data challenges.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at Jack & Jill/External Ats
✨Know Your Tech Stack
Familiarise yourself with the tools mentioned in the job description, like Python, SQL, and agentic coding tools such as Claude Code and Cursor. Be ready to discuss how you've used these technologies in past projects, especially in building data pipelines or working with unstructured data.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex data challenges. Think about times when you had to debug or optimise data systems, and be ready to explain your thought process and the impact of your solutions.
✨Understand the Business Context
Research Arctal and its role in the financial sector. Understand the importance of high-fidelity datasets for institutional clients. This will help you articulate how your skills can directly contribute to their mission and success.
✨Ask Insightful Questions
Prepare thoughtful questions that demonstrate your interest in the role and the company. Inquire about their current projects, team dynamics, or future goals. This shows you're not just interested in the position but also in how you can fit into their vision.