Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Lead Data Scientist

eFinancialCareers
Greater London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Lead Data Scientist - Remote

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data ScientistAbout Lendable

Lendable is on a mission to make consumer finance amazing: faster, cheaper, and friendlier. We're building one of the world's leading fintechpanies and are off to a strong start:

One of the UK's newest unicorns with a team of just over 600 people Among the fastest-growing techpanies 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 ( 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 1 Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting

About the role

We are excited to be hiring a new Lead Data Scientist for our team! Ideally, this role will suit someone with a proven background in building models in credit, lending, or other areas of financial services. 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 experiment with the latest machine learning techniquesbined with a rich data repository to build and deploy best-in-market risk models.

This role will primarily focus on our UK Cards business, but through team collaboration, you will be exposed to all areas of Lendable. Our team keeps up with the latest advancements in the industry through regular journal clubs.

Our team's objectives
The data science team develops proprietary machine learning modelsbining state-of-the-art techniques with a variety of data sources that inform scorecard development and risk management, optimise marketing and pricing, and improve operations efficiency. Research new data sources and unstructured data representation. Data scientists work across the business in a multidisciplinary capacity to identify issues, translate business problems into data questions, analyse and propose solutions. Deliver data services to a wide variety of stakeholders by engineering CLI programs / APIs. Design, implement, manage and evaluate experiments of products and services leading to constant innovation and improvement.
How you'll impact those objectives
Use your expertise to build and deploy models that contribute to the success of the business Stay up to date with the latest advancements in machine learning and proactively propose new approaches and projects that drive innovation. Learn the domain of products that Lendable serves, understanding the data that informs strategy and risk modelling. Extract, parse, clean and transform data for use in machine learning. Clearlymunicate results to stakeholders through verbal and writtenmunication. Mentor other data scientists and promote best practices throughout the team and business
Key Skills
Knowledge of machine learning techniques and their respective pros and cons. Ability tomunicateplex topics clearly and concisely Proficiency with creating ML models in Python with experiment tracking tools, such as MLFlow. Curiosity, creativity, resourcefulness and a collaborative spirit Interest in problems related to the financial services domain - a knowledge of Credit Cards is advantageous Confidentmunicator and contributes effectively within a team environment Experience mentoring or leading others Self-driven and willing to lead on projects / new initiatives
The interview process

We're not corporate, so we try our best to get things moving as quickly as possible. For this role, we'd expect:
A quick phone call with the talent team Take home task Task debrief Case study interview Meet the leadership team
Life at Lendable
The opportunity to scale up one of the world's most successful fintechpanies. Best-in-classpensation, including equity. You can work from home every Monday and Friday if you wish - on the other days, those based in the UKe together IRL at our Shoreditch office in London 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 ites to private health insurance We're an equal-opportunity employer and are looking to make Lendable the most inclusive and open workspace in London
Check out our blog! Job ID wQcEe9EbBJg3

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.

Seasonal Hiring Peaks for Data Science Jobs: The Best Months to Apply & Why

The UK's data science sector has matured into one of Europe's most intellectually rewarding and financially attractive technology markets, with roles spanning from junior data analysts to principal data scientists and heads of artificial intelligence. With data science positions commanding salaries from £30,000 for graduate data analysts to £140,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this intellectually stimulating and rapidly evolving field. Unlike traditional analytical roles, data science hiring follows distinct patterns influenced by business intelligence cycles, research funding schedules, and machine learning project timelines. The sector's unique combination of mathematical rigour, business impact requirements, and cutting-edge technology adoption creates predictable hiring windows that strategic professionals can leverage to advance their careers in extracting insights from tomorrow's data. This comprehensive guide explores the optimal timing for data science job applications in the UK, examining how enterprise analytics strategies, academic research cycles, and artificial intelligence initiatives influence recruitment patterns, and why strategic timing can determine whether you join a pioneering AI research team or miss the opportunity to develop the next generation of intelligent systems.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.

Why Now Is the Perfect Time to Launch Your Career in Data Science: The UK's Analytics Revolution

The United Kingdom stands at the forefront of a data science revolution that's reshaping how businesses make decisions, governments craft policies, and society tackles its greatest challenges. From the machine learning algorithms powering London's fintech innovation to the predictive models guiding Manchester's smart city initiatives, Britain's transformation into a data-driven economy has created an unprecedented demand for skilled data scientists that far outstrips the available talent. If you've been contemplating a career transition or seeking to position yourself at the cutting edge of the digital economy, data science represents one of the most intellectually stimulating, financially rewarding, and socially impactful career paths available today. The convergence of big data maturation, artificial intelligence mainstream adoption, business intelligence evolution, and cross-industry digital transformation has created the perfect conditions for data science career success.