# Support & Operations Analyst at Lendable > Hybrid · Mexico · Unspecified · Other · open. Source: https://alderhq.app/jobs/ashby%3Alendable%3Ab1df7e92-0ff6-471f-beab-0830c9f53e29 (read 2026-11-03). ## Facts (observed) - Company: [Lendable](https://alderhq.app/companies/lendable) - Location text: Mexico City, Mexico - Where it can be done from (inferred): Hybrid · Mexico (evidence: "Location: Mexico City, Mexico") - Posted: 2026-10-14 (20 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-03 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/lendable/b1df7e92-0ff6-471f-beab-0830c9f53e29 - Skills listed (inferred): SQL ## Pay and sponsorship - Posted pay: not posted - Licensed UK sponsor: registered as "Lendable Operations Ltd" (checked 2026-11-03, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers)) ## Description (the employer's text) ### About Lendable Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start: One of the UK’s most exciting unicorns with a team of over 800 people Among the fastest-growing tech companies in the UK Profitable since 2017 Backed by top investors including Balderton Capital and Goldman Sachs Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot) So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days. We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes. ### Join us if you want to Take ownership: you are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1 Work in small teams of exceptional people: Lendies are relentlessly resourceful. We challenge the status quo to solve problems and find smarter solutions Build the best technology in-house: we use new data sources, machine learning and AI to make machines do the heavy lifting ### About the Role Lendable is launching its credit card product in Mexico and building a founding local team. We're looking for someone to own the day-to-day operation of that product: the customer conversations, yes, but also the queues, the exceptions, the data behind them, and the tooling that makes all of it faster next month than it was this month. This is not a scripted support seat. Our support stack is heavily instrumented and increasingly AI-assisted, which means the routine answers are largely handled what's left is the interesting part: cases that don't fit the script, patterns nobody has noticed yet, and processes that still need a human to design them. You'll spend part of your week talking to customers and part of it figuring out why they had to contact us at all. We're a small team in a market we're still learning. The person who does well here is curious, comfortable being the one who doesn't wait to be told, and happy to wear whichever hat the day needs. ### What You'll Do ### 1. Own the daily operational queues, end to end Run the recurring card-ops routines: blocked accounts, failed card deliveries, payments that need reconciling, applications stuck mid-flow Take a case from first contact through to actual resolution, including the backend or ops step that fixes it — not just the reply to the customer Keep queues clean and decisions auditable, and know which cases genuinely need another team versus which ones you can close yourself ### 2. Investigate, don't just respond Dig into dashboards, internal tools, and customer records to work out what actually happened before deciding what to say Reconstruct timelines across systems — application, card, transactions, payments and form a view on root cause Spot irregularities early (fraud signals, broken flows, provider failures) and escalate with evidence and a hypothesis, not just a screenshot ### 3. Work alongside AI agents as part of your toolkit Use AI assistants and internal agents to triage, draft, summarise, and pull data — and know when their output is wrong and shouldn't be shipped Improve the prompts, macros, and knowledge sources those agents rely on when you see them getting things wrong or going stale Help us decide which repetitive work should be automated next, and what needs to stay human ### 4. Turn recurring problems into fewer problems Track what customers contact us about, quantify it, and bring the top patterns to Product, Risk, and Engineering with data attached Write and maintain the runbooks, help articles, and macros the rest of the team uses Reduce your own dependency on other teams: learn the internal tools, the SQL queries, and the ops scripts well enough to answer your own questions --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Alendable%3Ab1df7e92-0ff6-471f-beab-0830c9f53e29 and the date you read it. Observed facts come from the employer's public job board; location reach, level, family and skills are inferences.