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Lendable is a UK fintech unicorn (800+ employees, profitable since 2017, backed by Balderton Capital and Goldman Sachs) rebuilding consumer finance products—loans, credit cards, and car finance—with technology that gets money to customers in minutes instead of days. The company is expanding into the UK and US markets.
You'll join the Operations Science & Strategy team, sitting at the intersection of analytics, data science, and AI engineering. Working directly with senior operations leadership, you'll own special projects that diagnose demand drivers, uncover commercial opportunities, build KPI frameworks, and deploy automation that reduces cost-to-serve while improving customer outcomes.
Key responsibilities:
**Automation & AI Engineering:** Use Python and LLM APIs (e.g., OpenAI) to design and deploy automation that replaces manual customer service and finance processes. Build prototypes, test with real operations data, and scale successful ones into production workflows. Partner with PMs and engineers to operationalize AI-driven solutions.
**Demand Analytics & Strategy:** Analyze key operations demand drivers (contact per customer, reason drivers, seasonality, servicing behavior). Identify levers to reduce avoidable demand and improve customer outcomes. Build analytical models that drive decision-making around cost optimization and resourcing.
**KPI & Funnel Intelligence:** Build clear, robust KPI frameworks and funnel views across customer journeys. Translate data into commercial insight, operational efficiency recommendations, and productivity tracking. Create metrics that scale across new geographies, products, and teams.
**Work with Senior Leadership:** Collaborate directly with Ops Directors, Heads of CS/FS/Fraud/Complaints, and the COO on strategic initiatives. Turn raw data into narrative-driven recommendations that are simple, actionable, and commercially grounded. Own analytics for high-impact projects end-to-end.
The interview process includes a screening call with Python questions, a live technical Python interview, and final interviews with two senior leaders.
**Requirements:**
- 2–3 years of hands-on professional experience using Python
- Highly numerate with strong analytical reasoning
- Ability to independently structure analysis, build prototypes, and deliver insights
- Experience communicating data-driven recommendations to non-technical business stakeholders
**Nice-to-haves:**
- STEM degree
- Experience with dbt or modern data stacks
- Familiarity with LLMs, APIs, or interest in building AI automation
- Exposure to product, strategy, or operations environments
- Thrives in fast-paced, ambiguous environments
- Comfortable wearing multiple hats (Analyst, Data Scientist, AI Engineer, PM)
- Highly motivated, entrepreneurial mindset, excited by building the strongest operating model in fintech
