You will act as a super-IC managing a fleet of AI agents to turn 100,000+ unstructured financial PDFs into high-fidelity queryable datasets. Sitting between data science and engineering, you will design agentic workflows, encode human judgment into validation logic, and ensure total data reliability for global asset managers and banks.
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Data Scientist, AI Agents at Arctal
Join an elite 5-person team in London led by founders from Secondmind and Sylvera to redefine how institutional finance consumes data. As a Data Scientist for AI Agents, you won't just analyze data—you'll manage a fleet of autonomous agents that transform hundreds of thousands of complex financial PDFs into structured datasets. This is a high-intensity, technical role for someone fluent in Python and AI coding tools like Cursor who wants to own the delivery of high-stakes data for global banks and asset managers. If you're a data-obsessed IC ready to build at the frontier of agentic workflows, this is your next move.
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Location
London, United Kingdom
Compensation
£60-100k + Meaningful Equity
Company
Arctal
Role overview
Finance1-10 employees
Arctal builds structured datasets from unstructured financial documents using AI agents. Arctal's AI agents ingest documents at scale and output structured, validated datasets across transition and climate risk, sovereign and other areas. They build and operate the AI Agents for the data system, responsible for an expanding stream of reliable base data. These systems run continuously. Active in financial services, artificial intelligence, startups, finance technology, data, and based in London, UK.
What you will do
- Design and maintain data pipelines using AI agents, prompt chains, and human-in-the-loop checkpoints to extract data at scale.
- Build and encode sophisticated validation logic in Python and SQL to catch edge cases that standard LLM extractions miss.
- Manage the end-to-end data quality lifecycle, serving as the final line of defense for data accuracy before it reaches tier-one financial clients.
Who this is a fit for
- 1–5 years of experience as a Data Scientist or Analytics Engineer with deep proficiency in Python, SQL, and terminal-based workflows.
- AI-native professional who uses tools like Cursor or Claude Code for production-level work and understands agentic patterns over simple prompting.
- A data-obsessed builder who has experience wrangling messy, unstructured datasets and feels a personal responsibility for data integrity and precision.
Why this role is remarkable
- Work directly with founders including a former Sylvera founding member and a Cambridge ML expert who co-founded Secondmind.
- Join a high-output, 5-person team in Old Street where you'll automate yourself out of tasks daily to tackle increasingly complex financial data challenges.
- Take ownership of the entire delivery function with direct exposure to institutional customers and the frontier of agentic AI workflows.
How Jack & Jill work together
I get to know what you’re great at, then find roles you’d never find yourself.Ok, I'll go first. I'm Jack, an AI that gets to know you on a quick call, learning what you're great at and what you want from your career. Then I help you land your dream job by finding unmissable opportunities as they come up, supporting you with applications, interview prep, and moral support.
I recruit from Jack’s network and make the intro when I spot a great match.And I'm Jill, an AI Recruiter who talks to companies to understand who they're looking to hire. Then I recruit from Jack's network, making an introduction when I spot an excellent candidate.
Jack gets to know what you're great at and what you want next, then searches 15 million jobs daily and helps you discover roles at companies like this.
Meet Jack
What happens next?
Jack’s an AI agent for job searching and career coaching. He works for you.
Jill is the AI recruiter working for the company. She recruits from Jack’s network.
If your profile’s a match and Arctal wants to meet, Jill will make the intro. In the meantime, Jack will send you excellent alternatives.