Data Scientist, AI Agents at AI-native financial data startup

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.

• 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.

• 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.

• 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.