At a Glance
- Tasks: Build innovative credit risk models and dashboards to shape our lending decisions.
- Company: Fast-growing UK SME lender on a mission to support small businesses.
- Benefits: Competitive salary, equity, and hybrid working from our London office.
- Other info: Join a diverse team where your ideas matter and career growth is encouraged.
- Why this job: Be a foundational data hire and make a real impact in the fintech space.
- Qualifications: 2-5 years in data science with a focus on credit risk; Python and SQL skills required.
The predicted salary is between 60000 - 80000 € per year.
Lenkie is a fast-growing UK SME lender on a mission to give small businesses access to fair, fast, and flexible finance. We're at an exciting inflection point — scaling our lending book and building the data infrastructure that will power our credit decisions for years to come. This is a rare opportunity to be the foundational data science hire and have a genuine hand in shaping how we think about credit risk, model development, and data-driven decisioning in risk as well as other parts of the business.
About the job
We're looking for a (Senior) Data Scientist with deep credit risk experience to join us as one of our earliest data hires. You'll work closely with the Head of Credit, Credit Risk Manager and CTO to build our modelling capability from the ground up — from scorecard development and underwriting automation to portfolio analytics and early warning systems as well as Customer Lifetime Values. This isn't a role where you'll plug into an existing machine. You'll be defining how we do things, building the infrastructure, and helping recruit the team around you as we grow.
Key Responsibilities
- Build credit risk models - application scorecards, behavioural models, propensity models - across our SME lending products
- Create portfolio monitoring dashboards, MI packs, and early warning indicators for the credit and leadership teams
- Work with Open Banking, bureau, and alternative data sources to enrich our credit assessment
- Define data science best practices, tooling, and ways of working as the function grows
- Partner closely with Product, Engineering, and Credit to translate business problems into data solutions
- Support the Head of Credit and Credit Risk Manager on strategic projects — limit setting, pricing, risk appetite calibration
- Use your data science expertise for projects outside of credit risk, e.g. Customer Lifetime Value modeling.
Qualifications/Required Skills
- 2–5 years of experience in data science or quantitative analysis, with a strong focus on credit risk in a fintech or lending environment
- Hands-on experience building credit scorecards or risk models (application, behavioural, or collections)
- Proficiency in Python and SQL; experience with ML frameworks (scikit-learn, XGBoost, etc.)
- Familiarity with Open Banking data, bureau data (Experian, Equifax, TransUnion), or alternative data sources
- Comfort working in small, fast-moving teams where you have to be both strategic and hands-on
- Experience with SME lending is a strong plus (vs. consumer)
- Strong communicator — able to explain model outputs and data insights to non-technical stakeholders
How we reward performance
- Be a founding member of the data team with real ownership and influence
- Competitive salary + meaningful equity
- Hybrid working from our London office
- A mission you can get behind - helping small businesses access the finance they deserve
We’re building a diverse, inclusive and supportive team where everyone can do their best work. We welcome applications from people of all backgrounds, experiences and perspectives, and we do not discriminate based on age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation. If you require any reasonable adjustments during the recruitment process, please let us know.
Senior Data Scientist London employer: Lenkie Inc.
Lenkie is an exceptional employer for those looking to make a significant impact in the fintech space. As a Senior Data Scientist, you'll enjoy a competitive salary and equity while working in a hybrid model from our vibrant London office. With a strong focus on employee growth, a supportive and inclusive culture, and the opportunity to shape the future of credit risk modelling, Lenkie offers a unique environment where your contributions truly matter.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Lenkie or similar companies. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio of your past projects, especially those related to credit risk models. When you get the chance to chat with hiring managers, let your work speak for itself.
✨Tip Number 3
Be ready to discuss your thought process. In interviews, they’ll want to know how you approach problems. Practice explaining your methods and decisions clearly, especially when it comes to data-driven solutions.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of our mission to help small businesses thrive.
We think you need these skills to ace Senior Data Scientist London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role. Highlight your experience in credit risk and data science, and don’t forget to mention any hands-on projects you've worked on that relate to SME lending.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you’re excited about this opportunity at Lenkie. Share your passion for helping small businesses and how your skills can contribute to our mission.
Showcase Your Technical Skills:We want to see your proficiency in Python and SQL! Include specific examples of how you've used these tools in your previous roles, especially in building credit models or dashboards.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves.
How to prepare for a job interview at Lenkie Inc.
✨Know Your Credit Risk Models
Make sure you brush up on your knowledge of credit risk models, especially application scorecards and behavioural models. Be ready to discuss your hands-on experience in building these models and how they can be applied to Lenkie's SME lending products.
✨Showcase Your Technical Skills
Since proficiency in Python and SQL is crucial for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem or explain how you've used ML frameworks like scikit-learn or XGBoost in past projects.
✨Understand the Business Context
Familiarise yourself with Lenkie's mission and the challenges small businesses face in accessing finance. Be prepared to discuss how your data science expertise can translate into actionable insights that support their goals, particularly in credit risk and customer lifetime value modelling.
✨Communicate Clearly with Non-Technical Stakeholders
As a Senior Data Scientist, you'll need to explain complex data insights to non-technical team members. Practice articulating your thoughts clearly and concisely, using relatable examples to ensure everyone understands the value of your work.
