Data Lead

Wave Group; Greater London; On-site; GBP 80,000 - 100,000; Full time

Benefits offered by this job

Profit share

VISA sponsorship available

Job summary

Wave Group is seeking a Data Lead to transform unstructured financial documents into structured datasets for major financial institutions. This fully hands-on role requires you to dive into messy data, ensuring its quality while directing AI agents in extraction processes.

You will play a crucial role in guiding data accuracy and client communication, making sure the data provided is trustworthy. Ideal candidates will have 2-5 years of relevant experience with a deep obsession for data quality.

Qualifications

• 2-5 years of experience building datasets from unstructured sources.
• Fluency in Python and SQL, with pipeline debugging capability.
• Experience with LLMs in production environments.

Responsibilities

• Build datasets from raw financial documents.
• Direct AI agents to extract and validate data.
• Work closely with clients to explain methodologies.

Skills

Data quality obsession

Python

SQL

Web scraping

LLMs experience

AI-native tooling

Document parsing

Tools

Claude Code

OpenAI Agents SDK

Job description

Job Title: Data Lead (fully hands‑on, no management)

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)