Data Scientist, Credit & Analytics — Fintech Lending

Teya; Greater London; Híbrido; GBP 40 000 - 65 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Flexible hours

WellHub fitness partnership

Extended parental leave

Cycle-to-Work

Health insurance

Pension scheme

25 days leave

Office snacks

Central London office

Resumo da oferta

Teya, a fintech platform in London, is hiring a Data Scientist to join the Credit & Analytics team. You’ll develop credit risk and pricing models, explore data, and help deploy and monitor models used to inform credit decisions and portfolio performance.

Ideal candidates have up to 2 years in data science, a quantitative degree, and strong Python/SQL skills, with a passion for learning and impact in a high-growth environment.

Qualificações

• 0–2 years’ experience in data science or quantitative analysis.
• Degree in Mathematics, Statistics, Physics, Engineering or Computer Science.
• Solid grounding in statistics and core machine learning techniques.
• Working knowledge of Python and SQL with real-world data experience.

Responsabilidades

• Model development: build and test credit risk and pricing components under guidance.
• Data exploration: clean real-world datasets and engineer features for models.
• Analysis: study merchant behavior, repayment and product performance to answer business questions.
• Model monitoring: track performance and investigate drift or changes.
• Model deployment: assist deploying models onto the ML Platform and integrate into credit systems.
• Documentation: document work for easy understanding and reuse.
• Collaboration: work with Product, Engineering and Credit Strategy to grow skills.

Conhecimentos

Data science

Python

SQL

Statistics

Machine learning

Formação académica

Quantitative degree

Ferramentas

ML Platform

Descrição da oferta de emprego

Teya, a fintech platform in London, is hiring a Data Scientist to join the Credit & Analytics team. You’ll develop credit risk and pricing models, explore data, and help deploy and monitor models used to inform credit decisions and portfolio performance.

Ideal candidates have up to 2 years in data science, a quantitative degree, and strong Python/SQL skills, with a passion for learning and impact in a high-growth environment.