At a Glance
- Tasks: Build and deploy innovative machine learning models for credit risk in a fast-paced fintech environment.
- Company: Join Lendable, a leading fintech unicorn transforming consumer finance with cutting-edge technology.
- Benefits: Enjoy flexible working, health coverage, and delicious office meals while growing your career.
- Other info: Collaborative culture with opportunities for mentorship and professional growth.
- Why this job: Make a real impact in the financial sector and work with exceptional talent on exciting projects.
- Qualifications: Proven experience in machine learning, Python, and a passion for financial services.
The predicted salary is between 60000 - 80000 € 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 700 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 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 Senior Data Scientist for our team! Ideally, this role will suit someone with a proven background in building models ideally 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 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 machine learning models combining 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 credit risk modelling proactively proposing 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.
- Clearly communicate results to stakeholders through verbal and written communication.
- 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 to communicate sophisticated 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 loan or credit card underwriting is advantageous.
- Confident communicator and contributes effectively within a team environment.
- Experience mentoring or leading others.
- Self-driven and willing to lead on projects / new initiatives.
- Familiarity with data used within credit risk decisioning such as Credit Bureau data, especially across multiple geographies is an advantage.
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 people team
- Interview with hiring manager
- Take home task
- Task debrief
- Case study interview
- In person interview where you'll do your final round and have some lunch with the team
Life at Lendable:
- Winning team: the opportunity to scale up one of the world’s most successful fintech companies
- Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites
- Socials & connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls
- Health coverage: support for your physical and mental wellbeing, including private health cover
- Retirement & savings: long-term financial wellbeing through retirement savings plans
- Employee referral programme: earn a competitive bonus when you refer successful new team members
- Office meals & snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations
- Sustainable commuting: cycle-to-work and electric vehicle salary sacrifice schemes available in select locations
Please note: The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.
Senior Data Scientist - US Products in London employer: Lendable
Lendable is an exceptional employer, offering a dynamic work culture where innovation thrives and employees are empowered to make impactful decisions from day one. With a strong focus on employee growth, the company provides access to cutting-edge technology and mentorship opportunities, alongside flexible working arrangements and comprehensive health benefits, making it an ideal place for those looking to advance their careers in the fintech sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist - US Products in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current Lendable employees on LinkedIn. A personal introduction can make all the difference in getting your foot in the door.
✨Tip Number 2
Prepare for your interviews by researching Lendable's products and recent developments in fintech. Show us you’re genuinely interested in our mission and how your skills can contribute to our success.
✨Tip Number 3
Practice your problem-solving skills! Be ready to tackle case studies or technical challenges during interviews. We love seeing how you approach real-world problems, so think aloud and share your thought process.
✨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 us you’re serious about joining the Lendable team!
We think you need these skills to ace Senior Data Scientist - US Products in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with machine learning, credit risk modelling, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you're passionate about fintech and how you can contribute to Lendable's mission. Be sure to mention specific experiences that relate to the job description.
Showcase Your Projects:If you've worked on any interesting data science projects, don't hesitate to showcase them! Whether it's through a portfolio or links to GitHub, we love seeing practical applications of your skills and creativity.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen on joining our team at Lendable!
How to prepare for a job interview at Lendable
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning techniques and credit risk modelling. Be ready to discuss specific models you've built in the past, especially in financial services. This will show that you not only understand the theory but also have practical experience.
✨Understand Lendable's Mission
Familiarise yourself with Lendable's products and their unique selling points. Knowing how they rebuild consumer finance products and their approach to transparency will help you align your answers with their goals during the interview.
✨Prepare for Case Studies
Since you'll likely face a case study interview, practice breaking down complex problems into manageable parts. Think about how you would apply data science to real-world scenarios relevant to Lendable’s business, like optimising loan pricing or improving risk assessment.
✨Show Off Your Communication Skills
Being able to explain complex data science concepts clearly is crucial. Prepare to demonstrate how you can communicate findings to non-technical stakeholders. Use examples from your past experiences where you successfully conveyed technical information in an understandable way.