About Lendable Lendable is on a mission to make consumer finance amazing: faster, cheaper and friendlier. We're building one of the world's leading fintech companies and are off to a strong start:
One of the UK's newest unicorns with a team of just over 400 peopleAmong the fastest-growing tech companies in the UKProfitable since 2017Backed by top investors including Balderton Capital and Goldman SachsLoved 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 across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quoBuild the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy liftingAbout the role We are excited to be hiring a new Data Scientist into our team! Lendable is the market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science sits at the heart of this USP, developing the credit risk models to underwrite loan and credit card products.
You will have access to the latest machine learning techniques combined with a rich data repository to deliver best in market risk models.
Our teams' objectives The data science team develops proprietary behavioural models combining state of the art techniques with a variety of data sources that inform market-facing underwriting and pricing decisions, scorecard development, and risk management.Data scientists work across the business in a multidisciplinary capacity to identify issues, translate business problems into data questions, analyse and propose solutions.We self-serve with all deployment and monitoring, without a separate machine learning engineering team.Design, implement, manage and evaluate experiments of products and services leading to constant innovation and improvement.How you'll impact these objectives Learn the domain of products that Lendable serves, understanding the data that informs strategy and risk modelling is essential to being able to successfully contribute value.Rigorously search for the best models that enhance underwriting quality.Clearly communicate results to stakeholders through verbal and written communication.Share ideas with the wider team, learn from and contribute to the body of knowledge.Key skills Experience using Python and SQLStrong proficiency with PyData stackKnowledge of machine learning techniques and their respective pros and cons.Confident communicator and contributes effectively within a team environmentSelf-driven and willing to lead on projects / new initiativesNice to have Interest in machine learning engineeringStrong SQL and interest in data engineeringInterview process Initial call with TATake home taskTask debrief and case study interviewFinal interviews with Exec teamLife at Lendable (check out our Glassdoor page) The opportunity to scale up one of the world's most successful fintech companies.Best-in-class compensation, including equity.You can work from home every Monday and Friday if you wish - on the other days we all come together IRL to be together, build and exchange ideas.Our in-house chef prepares fresh, healthy lunches in the office every Tuesday-ThursdayWe care for our Lendies' well-being both physically and mentally, so we offer coverage when it comes to private health insuranceWe're an equal opportunity employer and are looking to make Lendable the most inclusive and open workspace in LondonCheck out our blog!
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