Customer Operations Team Leader (Auto Finance)

Lendable
Chatham
1 year ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer DBT

Lead Data Engineer - DBT

Senior Data Analyst - Customer Services

Senior Data Analyst (MI)

Data Scientist - Workforce Modelling

Data Scientist - Workforce Modelling

About Lendable

Lendable is on a mission to make consumer finance amazing:faster, cheaper and friendlier.
> We're building one of theworld's leading fintechcompanies and are off to a strong start:
> One of theUK's newest unicornswith a team of just over 400 people
> Among thefastest-growingtech companies in the UK
>Profitablesince 2017
> Backed by top investors includingBalderton CapitalandGoldman Sachs
>Lovedby customers with the best reviews in the market (4.9 across 10,000s of reviews onTrustpilot)

So far, we've rebuilt theBig Threeconsumer 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 across a broad remit.You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1
> Work insmall teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo
> Build thebest technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting


The Customer Service Department

The Customer Service department is responsible for working with customers who have queries about their loan/card/Motor from the application stage and support the end to end journey. Our primary role is to be the first point of contact for customers resolving queries at first point of contact and ensure customers needs are met.

Reporting to the Team Lead, the Customer Operations Executive will undertake customer queries via telephony, email and live chat. They will use skills and capability levels in the performance of their roles so that they can consistently achieve overall quality standards, embed processes and procedures to deliver good customer outcomes.

The Role

  • Undertake coaching to support colleagues and ensure coaching documentation reflects the level of support required.
  • Own the quality performance of their team, identify themes and trends and actively complete face to face and remote coaching of colleagues to help embed processes and deliver good customer outcomes.
  • Utilise management information reporting, alongside observation to identify opportunities for improvement and to highlight emerging trends for evaluation and focus.
  • Be accountable for employee engagement within their teams, responding and acting on emerging feedback to improve the overall colleague experience.
  • Where required, Interact directly with customers via voice/non voice as part of your role to ensure customer demand is managed in line with agreed service levels.
  • Complete live interaction marking, ensuring interactions are assessed against Lendable's quality assurance scorecard and delivering meaningful and actionable feedback/coaching.
  • Support Team's and other teams in a team leads absence

Your Profile

  • Financial services background in Loans/Cards/Motor
  • Strong written and verbal communication skillsRapport building with colleagues and customers
  • Ability to work to deadlines
  • Problem solving skills and with ability develop a range of initiatives to address coaching/training needs.
  • Good understanding of coaching as a discipline and able to apply knowledge and experience to coaching colleagues
  • Logical and methodical approach to evaluate situations and select appropriate solutions based on experience and an understanding of procedures.
  • Strong prioritisation skills, ability to organise and allocate and review work items to colleagues they are coaching
  • Resilient and calm approach when faced with difficult situations
  • Able to adapt written and verbal communication to an individuals needs.
  • Ability to operate comfortable in a fast paced and changing environment.
  • Vehicle finance experience from a dealer/broker desirable
  • Previous coaching or training experience desirable although not essential.
  • Previous people management skills desirable

Working Pattern

  • Monday – Friday 9am – 6pm (1 in 4 Saturday 9am - 6pm)
  • Based out of our office in Chatham
Life at Lendable (check out ourGlassdoor page)

> The opportunity to scale up one of theworld's most successfulfintech companies.
>Best-in-classcompensation, including equity.
> You can work from homeevery Monday and Fridayif you wish - on the other days we all come together IRL to be together, build and exchange ideas.
>Enjoy a fully stocked kitchen with everything you need to whip up breakfast, lunch, snacks, and drinks in the office every Tuesday-Thursday.
> We care for our Lendies' well-being both physically and mentally, so we offer coverage when it comes toprivate health insurance
> ?We're anequal opportunity employerand are looking to make Lendable the most inclusive and open workspace in London

Check out ourblog!



x1aZoZc2n8RqahAw7UAYQX

PI259998718

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.