At a Glance
- Tasks: Build and deploy innovative machine learning models to drive business success.
- Company: Join Lendable, a leading fintech unicorn with a collaborative culture.
- Benefits: Competitive salary, equity options, remote work flexibility, and health insurance.
- Why this job: Make a real impact in the fintech space while working with cutting-edge technology.
- Qualifications: Experience in data science, machine learning, and financial services preferred.
- Other info: Dynamic team environment with opportunities for mentorship and career 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 are 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 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)
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. Data Science sits at the heart of this USP, developing the credit risk models to underwrite loan and credit card products. 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:
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 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 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.
Senior Data Scientist employer: Lendable
Contact Detail:
Lendable Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees at Lendable on LinkedIn. A friendly message can go a long way in getting your foot in the door and showing your genuine interest in the company.
✨Tip Number 2
Prepare for the interview by brushing up on your machine learning knowledge. Be ready to discuss your past projects and how they relate to credit risk modelling. We want to see your passion and expertise shine through!
✨Tip Number 3
Don’t underestimate the power of a good case study. Practice solving real-world problems related to financial services. This will help you think on your feet during the interview and demonstrate your problem-solving skills.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining our team at Lendable. Let’s make it happen!
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Show Your Passion for Data: When writing your application, let us see your enthusiasm for data science! Share specific examples of projects you've worked on, especially in credit or lending, to demonstrate your expertise and how it aligns with our mission at Lendable.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Senior Data Scientist role. Highlight relevant skills and experiences that match the job description, particularly around machine learning and financial services. We love seeing candidates who take the time to connect their background to what we do!
Be Clear and Concise: In your written application, clarity is key! Use straightforward language to explain complex concepts, especially when discussing your experience with machine learning models. We appreciate candidates who can communicate effectively, as this is crucial for collaborating with our team.
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’re considered for the role. Plus, it shows you’re proactive and keen to join our awesome 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 their applications in credit risk modelling. Be ready to discuss specific models you've built, the challenges you faced, and how you overcame them. This will show that you not only have the technical skills but also the practical experience to back them up.
✨Understand Lendable's Mission
Familiarise yourself with Lendable's goals and how they use technology to help people get credit and save money. Being able to articulate how your skills can contribute to their mission will set you apart. Show enthusiasm for their innovative approach and be prepared to suggest how you could drive further advancements.
✨Prepare for the Case Study
Since there's a case study interview, practice analysing data sets and presenting your findings clearly. Think about how you would approach real-world problems related to credit and lending. This is your chance to showcase your analytical skills and creativity in problem-solving.
✨Communicate Clearly
During the interview, focus on communicating complex ideas in a simple way. Lendable values clear communication, so practice explaining your past projects and results succinctly. Remember, it's not just about what you know, but how well you can share that knowledge with others.