Senior Data Scientist, Credit Risk – Fintech (London)

YouLend; Camden Town; Hybrid; GBP 80,000 - 100,000; Full time

Benefits offered by this job

Private Medical Insurance (via Vitalty

EAP with Health Assured

Enhanced Maternity and Paternity Leave

Great office space in Central London

Subsidised lunch

Deliveroo allowance

Monthly in-office masseuse

Team and Company socials

Sports clubs

Job summary

YouLend in London is seeking a Senior Data Scientist to join the Credit Risk team. This hybrid role will be based at our London headquarters, applying advanced analytics and machine learning to shape embedded finance.

You will develop and refine Probability-of-Default and Revenue-Forecasting models while transforming data-driven insights into business decisions. Collaborating with cross-functional teams, you will ensure robust data pipelines and contribute to the model lifecycle and MLOps

Qualifications

• Experience as a data scientist in fintech.
• Proficiency in Python and SQL for data manipulation and modeling.
• Hands-on experience with a range of ML algorithms and MLOps practices.
• Ability to translate data into actionable insights for technical and non-technical audiences.
• Experience with financial/transactional datasets is a plus.

Responsibilities

• Analyse large datasets to uncover patterns informing business decisions.
• Build and deploy ML models to forecast outcomes and detect fraud.
• Develop algorithms for pricing or risk assessment.
• Create visualisations and dashboards to communicate findings to stakeholders.
• Collaborate with risk managers, engineers, and commercial teams to integrate insights.
• Partner with data/ML engineering to ensure robust data pipelines.
• Contribute to MLOps and model lifecycle best practices.

Skills

Python

SQL

ML algorithms

MLOps

Data visualization

Stakeholder communication

Fintech domain knowledge

Job description

YouLend in London is seeking a Senior Data Scientist to join the Credit Risk team. This hybrid role will be based at our London headquarters, applying advanced analytics and machine learning to shape embedded finance.

You will develop and refine Probability-of-Default and Revenue-Forecasting models while transforming data-driven insights into business decisions. Collaborating with cross-functional teams, you will ensure robust data pipelines and contribute to the model lifecycle and MLOps