At a Glance
- Tasks: Develop cutting-edge credit risk models using machine learning and data analysis.
- Company: Join Lendable, a fast-growing fintech unicorn transforming consumer finance.
- Benefits: Competitive salary, equity options, remote work flexibility, and health insurance.
- Why this job: Make a real impact in the fintech space with innovative technology and a supportive team.
- Qualifications: Experience in Python, SQL, and machine learning techniques; strong communication skills.
- Other info: Collaborative environment with opportunities for personal and professional growth.
The predicted salary is between 36000 - 60000 £ per year.
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 newest unicorns with a team of just over 600 people
- Among the fastest-growing tech companies in the UK
- Profitable since inception
- 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 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 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. This role will primarily focus on our US unsecured loans and credit cards business.
Our team's 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 those 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 SQL.
- Strong proficiency with data manipulation including packages like NumPy, Pandas.
- Knowledge of machine learning techniques and their respective pros and cons.
- Confident communicator and contributes effectively within a team environment.
- Self driven and willing to lead on projects / new initiatives.
Nice to have
- Prior experience of credit risk for consumer lending or credit cards, especially for the US market.
- Interest in machine learning engineering.
- Strong SQL and interest in data engineering.
The interview process
- Initial call with TA
- Take home task
- Task debrief and case study interview
- Final interviews with leadership team
Life at Lendable
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, those based in the UK come together in person 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 it comes to private health insurance. We're an equal-opportunity employer and are looking to make Lendable the most inclusive and open workspace in London.
Data Scientist in England employer: Lendable
Contact Detail:
Lendable Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in England
✨Tip Number 1
Get to know Lendable inside out! Research their products, values, and recent news. This will help you tailor your conversations during interviews and show that you're genuinely interested in being part of their mission.
✨Tip Number 2
Practice your data science skills with real-world problems. Use platforms like Kaggle to work on projects that mimic what Lendable does. This hands-on experience will give you great talking points during interviews.
✨Tip Number 3
Network like a pro! Connect with current Lendable employees on LinkedIn, attend fintech meetups, or join relevant online communities. Building relationships can give you insider tips and potentially a referral.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the team at Lendable.
We think you need these skills to ace Data Scientist in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role at Lendable. Highlight your experience with Python, SQL, and any machine learning techniques you've used. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share why you're excited about working at Lendable and how you can contribute to our data science team. Be genuine and let your personality come through – we love that!
Showcase Your Projects: If you've worked on relevant projects, whether in a professional or personal capacity, make sure to mention them. We’re keen to see how you’ve applied your data skills in real-world scenarios, especially in credit risk or consumer lending.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team. Let’s get started on this journey together!
How to prepare for a job interview at Lendable
✨Know Your Data Science Stuff
Make sure you brush up on your Python and SQL skills before the interview. Be ready to discuss your experience with data manipulation using libraries like NumPy and Pandas, as well as any machine learning techniques you've used. This will show that you're not just familiar with the tools, but that you can apply them effectively.
✨Understand Lendable's Mission
Dive deep into Lendable's mission and the products they offer. Knowing how their technology helps customers get credit and save money will help you align your answers with their goals. Be prepared to discuss how your skills can contribute to their objectives in the US unsecured loans and credit cards market.
✨Communicate Clearly
Since you'll need to share your findings with stakeholders, practice explaining complex data concepts in simple terms. Think about examples from your past where you had to communicate results or ideas to non-technical team members. This will demonstrate your ability to be a confident communicator within a team.
✨Show Initiative and Curiosity
Lendable values self-driven individuals who are willing to lead projects. Prepare to discuss instances where you've taken ownership of a project or initiative. Also, express your interest in learning more about machine learning engineering and how it can enhance your work as a Data Scientist.