At a Glance
- Tasks: Develop machine learning models to enhance credit card underwriting and pricing.
- Company: Lendable, a forward-thinking company in Greater London.
- Benefits: Hybrid/remote work, flexible hours, and opportunities for personal growth.
- Other info: Collaborative culture with room to shape your career path.
- Why this job: Join a dynamic team and make a real impact on customer management.
- Qualifications: Experience in data science and a passion for problem-solving.
The predicted salary is between 50000 - 70000 € per year.
Lendable in Greater London is seeking a Data Scientist to join our Cards Data Science team. This role focuses on developing machine learning models for our UK credit cards business to enhance underwriting, pricing, and customer management.
You will work with large datasets and collaborate with cross-functional teams to identify opportunities and deliver impactful solutions. We value intellectual curiosity and a collaborative mindset, with significant flexibility to shape your trajectory within the company.
Data Scientist, Growth & Underwriting (Hybrid/Remote) in London employer: Lendable
Lendable is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for Data Scientists looking to make a meaningful impact in the financial sector. With a focus on employee growth and development, we offer flexible working arrangements and the opportunity to work with cutting-edge technology on real-world challenges in the vibrant Greater London area. Join us to be part of a team that values your contributions and encourages you to shape your career path.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist, Growth & Underwriting (Hybrid/Remote) in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Lendable on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your machine learning projects, especially those relevant to credit cards or customer management. This will help you stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common data science interview questions and case studies. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining the Lendable team.
We think you need these skills to ace Data Scientist, Growth & Underwriting (Hybrid/Remote) in London
Some tips for your application 🫡
Show Your Passion for Data:When writing your application, let your enthusiasm for data science shine through! Share specific examples of projects or experiences that highlight your skills in developing machine learning models and working with large datasets.
Tailor Your CV and Cover Letter:Make sure to customise your CV and cover letter for the Data Scientist role at Lendable. Highlight relevant experiences that align with the job description, especially those related to underwriting, pricing, and customer management.
Be Clear and Concise:Keep your application clear and to the point. Use straightforward language and avoid jargon unless it’s necessary. We want to see your thought process, so make it easy for us to understand your ideas and contributions.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Lendable
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning models and data analysis techniques. Be ready to discuss specific projects you've worked on, especially those that relate to underwriting or pricing in the financial sector.
✨Show Off Your Collaboration Skills
Since this role involves working with cross-functional teams, be prepared to share examples of how you've successfully collaborated with others. Highlight any experiences where you’ve had to communicate complex data insights to non-technical stakeholders.
✨Demonstrate Intellectual Curiosity
Lendable values curiosity, so come armed with questions about their current data practices and challenges. This shows you're not just interested in the role but also eager to contribute to their growth and innovation.
✨Be Ready for Problem-Solving Scenarios
Expect some scenario-based questions where you'll need to demonstrate your analytical thinking. Practice articulating your thought process clearly, as they’ll want to see how you approach problem-solving in real-world situations.
