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About the Role
We are looking for a Data Scientist to join the Credit & Analytics team to help build the models that underpin our lending products. You will support the development of credit risk and pricing models, working across the model lifecycle from data exploration to deployment and monitoring. Your work will contribute to live products used by our Members from day one.
Responsibilities
- Build and test components of credit risk and pricing models, under guidance from senior team members.
- Explore internal and external data sources, clean and prepare real-world datasets, and engineer features that could improve our models.
- Carry out analysis of merchant behaviour, repayment performance and product performance to answer well-defined business questions.
- Help track model performance, flag changes or drift, and support investigations into what is driving them.
- Support Data Engineering with deploying models onto the ML Platform and integrating them into the credit decisioning system.
- Document your work clearly so models and analysis are easy to understand, review and build on.
- Work closely with Product, Engineering, Data Engineering and Credit Strategy, and actively seek feedback from senior data scientists to develop your technical and commercial skills.
Requirements
- 0–2 years' experience in data science, quantitative analysis or a related field.
- Degree in a quantitative field such as Mathematics, Statistics, Physics, Engineering, Computer Science or a related discipline.
- Solid grounding in statistics and an understanding of core machine learning techniques.
- Working knowledge of Python and SQL, with experience handling and analysing 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.
- Eagerness to learn, take on feedback and grow within a collaborative team.
- Exposure to credit risk modelling or financial services is a plus.
Skills
- Python
- SQL
- Statistics
- Machine learning techniques
- Data exploration
- Feature engineering
- Model monitoring
- Model deployment
Location
- Central London
Work Type
- Flexible working hours
- Office environment
Experience Level
- 0-2 years experience
Education Level
- Degree in a quantitative field
Benefits
- Flexible working hours
- Physical and mental health support through WellHub (gym access, therapy, meditation, digital fitness/nutrition apps)
- Extended and improved maternity and paternity leave choices
- Cycle-to-Work Scheme
- Health and Life Insurance
- Pension Scheme
- 25 days of Annual Leave plus Bank Holidays
- Office snacks
About the Company
- Teya is building a financial platform for local businesses across Europe, with simple tools, thoughtful design, and real human support.
- We move fast, care about quality, stay close to the detail, and believe great performance and genuine hospitality go hand in hand.
- We want to build meaningful products, solve real problems, and make a genuine difference for local businesses.
Equal Opportunity
- 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.
- We are committed to ensuring that every candidate has a fair and accessible experience with us and will provide reasonable adjustments at any stage of the recruitment process.