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Data Analyst

Organismo
Fundingcircle
País
🇬🇧 Reino Unido
Lugar
London
Puestos
1
Tipo de vínculo
privado

Descripción del puesto

We’re on a mission to back the UK’s small businesses like no one else 🚀 Small businesses are the backbone of the economy, and we’re here to help them win. We’ve built a platform that uses clever data to get them the funding they need in minutes, not weeks. At Funding Circle, we have the restless energy of a fintech start-up with the stability of a public company. It’s a unique mix that gives Circlers the autonomy to take ownership and the scale to make an impact that truly counts. We’re a high-performing team that chooses to lift each other up. We challenge, we champion, and we have each other’s backs - because we know that when we stand together, we move faster and build better. The impact is real: Last year alone, the businesses on our platform generated £7.2bn for the UK economy 📈 Come and join a mission that matters! [ Read our Impact Report ] | [ See our Trustpilot ] The role ⚡ 📍 London (Hybrid) | 🤝 3 days in the office | 💰 Competitive Salary + Benefits This role sits within the Second Line Credit Strategy team. We provide independent oversight of credit risk models, strategies, and the data assets that underpin them. You will own a critical piece of our data infrastructure and play a hands-on role in making sure the team can do its best analytical work. The primary steward of the modelled datasets the Credit Risk team relies on daily: maintaining field logic, monitoring data quality, and ensuring the data as well as the dictionary remains accurate and fit for purpose. Creating new tables and pipelines as the team’s analytical needs evolve, working to a high standard of code quality and documentation. Proactively identify anomalies, breaks, and drift in the datamart, and investigate root causes before they affect downstream users. Be the go-to person for data questions from analysts and model validators, and will maintain clear documentation so others can self-serve confidently. Working closely with the central Data to align on tooling, infrastructure, and

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