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About the Role
We’re building a financial platform for local businesses across Europe, focusing on simple tools, thoughtful design, and real human support. This role involves using data and models to improve business outcomes across various domains, from understanding merchant churn to forecasting transaction volumes and modelling credit risk. You will work on the full model lifecycle, from exploration to deployment and monitoring, ensuring statistical soundness and delivering real business value through collaboration with senior data scientists and stakeholders.
Responsibilities
- Support the translation of business problems into analytical and modelling tasks, contributing ideas and exploring alternative approaches.
- Develop and enhance predictive models across domains such as churn, lead conversion and volume forecasting, under guidance from senior team members.
- Collaborate with Data Engineering and Engineering to assist the deployment of models onto the ML Platform and integration into production systems.
- Help monitor model performance, investigate performance changes or drift, and contribute to model improvements over time.
- Explore internal and external data sources, engineer features, and assess their predictive value across a range of modelling problems.
- Work closely with Product, Engineering, Data Engineering and commercial teams to ensure modelling work supports operational and commercial goals.
Requirements
- Hands-on experience of predictive modelling applied to real commercial problems, ideally in a fintech/scale-up.
- 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.
Skills
- Python
- SQL
- Machine learning techniques
- Predictive modelling
Location
- Central London
Work Type
- Flexible working hours
- Office-based
Experience Level
- Early career with hands-on predictive modelling experience
Education Level
- Degree in a quantitative field such as Mathematics, Statistics, Engineering or related discipline
Benefits
- Flexible working hours
- Physical and mental health support through GymPass (1,500+ gyms, 1-1 therapy, meditation, digital fitness/nutrition apps)
- Extended and improved maternity and paternity leave
- Cycle-to-Work Scheme
- Health and Life Insurance
- Pension Scheme
- 25 days of Annual Leave plus Bank Holidays
- Office snacks
- Friendly, comfortable, and informal office environment
About the Company
- Teya was founded on the belief that local businesses deserve better financial services.
- We are building a financial platform for local businesses across Europe.
- We aim to provide 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.
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 encourage candidates to let us know if they require any reasonable adjustments at any stage of the recruitment process.