At a Glance
- Tasks: Develop and enhance credit risk models to support lending products for small businesses.
- Company: Join Teya, a fintech championing local businesses across Europe.
- Benefits: Enjoy continuous learning, a supportive community, and comprehensive benefits.
- Why this job: Make a real impact in a fast-growing fintech while deepening your expertise.
- Qualifications: Hands-on credit modelling experience and a degree in a quantitative field.
- Other info: Inclusive workplace committed to diversity and equal opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Hello! We’re Teya. Teya is a payment and software service provider, headquartered in London serving small, local businesses across Europe. Founded in 2019, we build easy to use, integrated tools that enable our members to accept payments and boost business performance. At Teya we believe small, local businesses are the lifeblood of our communities. We’re here because we don’t believe there’s a level playing field that gives small businesses with a fighting chance against the giants of the high street. We’re here because we see banks and legacy service providers making things harder for them. We don’t think the best technology or the best service should be reserved for those with the biggest headquarters. We’re here to fight for a future where small, local businesses can thrive, and to commit the same dedication they offer all of us. Become a part of our story. We’re looking for exceptional talent to join our mission. We offer a chance to create impact in a high-energy and connected culture, while benefiting from continuous learning opportunities, a supportive community which is proud to serve our mission, and comprehensive benefits.
Your Mission: We’re looking for a Data Scientist to join the Credit team at Teya to support the development of the credit risk and pricing models that underpin our lending products. This role will contribute directly to the delivery of our new lending products to small businesses across multiple geographies. You will work on modelling initiatives across the full model lifecycle, from data exploration and feature development through to model deployment and performance monitoring. You will use your strong quantitative background to ensure models are developed in a statistically sound way. Collaborating with senior data scientists and stakeholders across Credit Strategy, Product, Engineering and Data Engineering, you will ensure models are well-understood and deliver real business value. This is an excellent opportunity for someone early in their career who has hands-on credit modelling experience and wants to deepen their expertise within a fast-growing fintech.
Responsibilities:
- Problem solving: Support the translation of credit business problems into analytical and modelling tasks, contributing ideas and exploring alternative approaches.
- Model development: Develop and enhance components of credit risk models and risk-based pricing frameworks, under guidance from senior team members.
- Model deployment: Collaborate with Data Engineering to assist the deployment of models onto the ML Platform and integration into the credit decisioning system.
- Model monitoring: Help monitor model performance, investigate performance changes or drift, and contribute to model improvements over time.
- Data exploration: Explore internal and external data sources, engineer features, and assess their predictive value for credit modelling.
- Collaboration: Work closely with Product, Engineering, Data Engineering and Credit Strategy to ensure modelling work supports operational and commercial goals.
Requirements:
- Hands-on experience of credit risk modelling, ideally in SME lending for a fintech / scale-up etc.
- Degree in a quantitative field such as Mathematics, Statistics, Engineering or related discipline.
- Strong applied quantitative skills, including use of machine learning techniques.
- Proficiency in Python and SQL, with experience working with real-world datasets.
- Ability to explain analytical work clearly to both technical and non-technical stakeholders.
- Curious, pragmatic, and commercially minded, with a desire to understand how models drive business outcomes.
Teya is proud to be an equal opportunity employer. We are committed to creating an inclusive environment where everyone regardless of race, ethnicity, gender identity or expression, sexual orientation, age, disability, religion, or background can thrive and do their best work. We believe that a diverse team leads to better ideas, stronger outcomes, and a more supportive workplace for all. If you require any reasonable adjustments at any stage of the recruitment process whether for interviews, assessments, or other parts of the application—we encourage you to let us know. We are committed to ensuring that every candidate has a fair and accessible experience with us.
Data Scientist - Credit Risk employer: Teya Services Ltd.
Contact Detail:
Teya Services Ltd. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Credit Risk
✨Tip Number 1
Network like a pro! Reach out to people in the fintech space, especially those working at Teya or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your credit risk models or any relevant projects. This is your chance to demonstrate your hands-on experience and quantitative skills in a way that stands out.
✨Tip Number 3
Prepare for the interview by brushing up on your Python and SQL skills. Be ready to discuss how you've used these tools in real-world datasets, as this will be key in showing your fit for the role.
✨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 genuinely interested in joining our mission at Teya.
We think you need these skills to ace Data Scientist - Credit Risk
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role at Teya. Highlight your hands-on experience with credit risk modelling and any relevant projects you've worked on. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you're passionate about supporting small businesses through data science. Share your journey, your motivations, and how you can contribute to our team. Keep it engaging and personal!
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Python and SQL! We’re keen to see examples of how you’ve used these tools in real-world datasets. If you have any projects or case studies, include them to demonstrate your expertise.
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. Plus, we love seeing applications come through our own platform!
How to prepare for a job interview at Teya Services Ltd.
✨Know Your Models Inside Out
Make sure you can discuss your previous credit risk models in detail. Be prepared to explain the methodologies you used, the challenges you faced, and how you overcame them. This shows your hands-on experience and understanding of the model lifecycle.
✨Brush Up on Your Technical Skills
Since proficiency in Python and SQL is crucial for this role, ensure you're comfortable with both. Practice coding problems or data manipulation tasks that could come up during the interview. Being able to demonstrate your technical skills will set you apart.
✨Understand Teya's Mission
Familiarise yourself with Teya’s commitment to supporting small businesses. Think about how your work as a Data Scientist can contribute to this mission. Showing that you align with their values will resonate well with the interviewers.
✨Prepare for Collaboration Questions
Expect questions about how you work with cross-functional teams. Be ready to share examples of past collaborations, especially with non-technical stakeholders. Highlighting your ability to communicate complex ideas clearly will be key in demonstrating your fit for the role.