At a Glance
- Tasks: Lead data processing from raw documents to structured datasets using AI agents.
- Company: Exciting start-up transforming financial data for major institutions.
- Benefits: Up to £100k salary, profit share, equity, and a dynamic work environment.
- Other info: Join a small, innovative team with significant growth potential.
- Why this job: Own your work and make a real impact in a high-visibility role.
- Qualifications: 2-5 years of hands-on data experience and strong Python/SQL skills.
The predicted salary is between 90000 - 100000 £ per year.
Salary: up to ~£100k + profit share
Equity: 0.75 - 1%
Location: Old Street (4-5 office days/week)
About the company
This early stage start-up is processing hundreds of thousands of unstructured financial documents into clean, structured datasets for some of the world's largest financial institutions - producing the output of 50, with a team of 5. Forecasting £1.5m revenue within their first 12 months, they have immense potential - not based on hype or inflated valuations, but rather achieving mega productivity through intelligent application of AI agents. Their mid-term goal is ~£50m revenue with a sub-30 person team.
What's in it for you?
- Profit share.
- Cash in your account on a regular basis - not a promise of a huge payout IF the company succeeds and sells.
About the role
At most data companies, a dataset is the output of a large analyst team. Here, it's the output of a fleet of AI agents - directed by one person who stakes their reputation on it being right. That's this role. You're not downstream. You're not cleaning data someone else built. You start from the source – raw documents, filings, internet data – and you build the dataset. You're the reason institutional clients – banks, hedge funds, investment firms – trust the data. AI agents do the extraction. You direct them, interrogate the output, catch what they miss and encode your judgement into validation systems that make the whole pipeline better over time. You'll also work directly with clients, explaining methodology to sophisticated buyers who need to understand what they're relying on. This isn't QA. It's the highest-ownership, most client-visible position in the company. Your name will be on the data. And for that, you'll have a very senior seat at the table.
Must have requirements
- Roughly 2-5 years working directly with data at a company where data is the core product – not as an analyst consuming clean datasets, but building them from messy, unstructured sources.
- Demonstrable obsession with data quality – you know what great data looks like because you've spent time making it from scratch.
- You go to the row level. A missing data point or unexplained anomaly bothers you until it's resolved – not flagged and forgotten.
- Genuinely AI-native: you've been using agentic tooling long enough to have opinions on it – Claude Code, Cursor, OpenAI Agents SDK or equivalent, used on daily basis.
- Python and SQL fluent – you've built and debugged pipelines, not just queried tables.
- Comfortable in the terminal, in codebases and in real-world messy data environments.
- Experience at a financial data provider (Bloomberg, Refinitiv, Preqin, FactSet etc.) or in quant/ESG research.
- You've built agents yourself – not just used them.
- Experience with LLMs in production / agentic workflow design.
- Web scraping and document parsing at scale.
- Experience in a small team (2-30 people) where you owned the whole function.
VISA sponsorship is available if needed (but you need to be already living in the UK).
Data Lead in London employer: Wave Group
At Wave Talent, we pride ourselves on being an exceptional employer, offering a unique opportunity for the Founding BDR to shape the future of our fast-growing fintech. With a vibrant work culture that encourages innovation and direct access to leadership, employees benefit from a range of perks including a premium membership to our investor collective and a gym membership. Our commitment to employee growth is evident as you will be at the forefront of building our outbound engine, allowing you to develop your skills in a dynamic environment while contributing to our impressive year-on-year growth.
