At a Glance
- Tasks: Lead AI-driven data processing and build structured datasets from raw financial documents.
- Company: Exciting early-stage start-up with massive growth potential in the fintech space.
- Benefits: Competitive salary up to £100k, profit share, and a dynamic work environment.
- Other info: VISA sponsorship available; work in a collaborative team with cutting-edge AI technology.
- Why this job: Make a real impact by ensuring data quality for top financial institutions.
- Qualifications: 2-5 years of data experience, Python and SQL fluency, and a passion for data quality.
The predicted salary is between 90000 - 100000 € per year.
Salary: up to ~£100k + profit share
Location: Old Street (4-5 office days/week)
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.
Cash in your account on a regular basis - not a promise of a huge payout IF the company succeeds and sells.
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.
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. Your name will be on the data.
- 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.
- 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 a 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.
Bonus points for:
- Experience at a financial data provider (Bloomberg, Refinitiv, Preqin, FactSet etc.)
- Web scraping and document parsing at scale.
VISA sponsorship is available if needed (but you need to be already living in the UK).
AI Delivery Lead/Data Analyst in City of London employer: Wave Group
Join an innovative early-stage start-up in Old Street, where your contributions as an AI Delivery Lead/Data Analyst will directly impact the financial data landscape. With a strong focus on employee growth and a culture that values data quality and integrity, you'll work alongside a small, dedicated team to transform unstructured financial documents into reliable datasets for top-tier clients. Enjoy competitive compensation, including profit sharing, and the opportunity to be at the forefront of AI-driven data solutions in a dynamic and supportive environment.
StudySmarter Expert Advice🤫
We think this is how you could land AI Delivery Lead/Data Analyst in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at companies you're interested in. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or a GitHub repository showcasing your data projects. This is your chance to demonstrate your obsession with data quality and your ability to build datasets from scratch.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with Python, SQL, and AI tools. We want to see how you tackle real-world messy data problems!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace AI Delivery Lead/Data Analyst in City of London
Some tips for your application 🫡
Show Your Data Passion:When you're writing your application, let your enthusiasm for data shine through! Share specific examples of how you've tackled messy datasets and turned them into something useful. We love seeing that obsession with data quality!
Be AI-Native:Make sure to highlight your experience with AI tools in your application. We want to know how you've used agentic tooling like OpenAI Agents SDK or similar in your work. This is your chance to show us you're genuinely AI-native!
Get Technical:Don’t shy away from showcasing your technical skills! Mention your fluency in Python and SQL, and any experience you have building or debugging data pipelines. We’re looking for someone who’s comfortable in the terminal and can handle real-world data challenges.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to see your application in the right context. Plus, it shows you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Wave Group
✨Know Your Data Inside Out
Before the interview, dive deep into your past experiences with data. Be ready to discuss specific projects where you transformed unstructured data into clean datasets. Highlight your obsession with data quality and how you've tackled anomalies in the past.
✨Show Off Your AI Tooling Skills
Familiarise yourself with the AI tools mentioned in the job description. Be prepared to share your opinions on them and how you've used similar tools in your previous roles. This will demonstrate your genuine AI-native mindset and your ability to leverage technology effectively.
✨Brush Up on Python and SQL
Make sure you're comfortable discussing your experience with Python and SQL. Prepare to talk about specific pipelines you've built or debugged, and be ready to tackle any technical questions that may come your way. Practical examples will make your skills stand out.
✨Understand the Financial Landscape
Since this role involves working with financial institutions, it’s crucial to have a grasp of the financial data landscape. Research the companies mentioned in the job description and be ready to discuss how your background aligns with their needs. This shows you're not just a data expert but also understand the industry context.
