Data Lead

Description:

Having raised over £7m at seed stage, this FinTech company is shaking up the payments space with their innovative real-time price comparison solutions, making card payments a lot fairer and cheaper for smaller businesses and their customers 🤝

With a host of very impressive investors backing this venture (same folk who invested early in the likes of Spotify, Klarna, Zopa, Citymapper, Curve and Trustpilot), and working in collaboration with the world's largest players in payments, this company is causing the biggest change to how businesses access card payments in over two decades.

Role overview

As the company's first data hire, you’ll be tasked with designing, building and owning their data stack. You’ll also be responsible for applying your expertise in quantitative analysis to understand how their users behave. Your insights will feed into data products that you’ll own, as well as into the wider product strategy.

Reporting directly to the CTO/founder and working alongside the founding employees, you'll have a huge impact on the business from day 1 - you'll get to experiment and built innovative products at pace & scale 🚀

✅ Must have requirements:

• Wide breadth of data experience, with a solid foundation in Data Science
• Obsession with data - we're looking for inquisitive people, passionate about crunching analysis and discovering unobvious patterns
• Experience designing, building and maintaining end to end data stacks (data pipelines, data infrastructure, data warehousing etc.)
• Experience working in a fast-paced, high-performance environment of unstructured nature (ideally an early stage start-up/scale-up) - we're looking for someone who thrives in ambiguity and likes to work things out by themselves rather than having a strictly predefined scope
• Cloud infrastructure experience - AWS is highly desirable, but GCP and Azure backgrounds are also ok
• Commercial mindset / understanding of wider business strategy

👍 Bonus points for:

• Experience working as the 1st/only Data hire in a business
• Familiarity with AI / ML
• Experience with data orchestration and data warehousing
• Experience with DBT and Terraform
• Strong academic background