Senior Decision Scientist, SME Lending (Hybrid/Remote)

Love Finance Limited; Birmingham; Hybrid; GBP 54,000 - 90,000; Full time

Job summary

Lovey in the UK is seeking a Senior Decision Scientist to lead the development of credit decisioning models across SME lending. You will own the end-to-end model lifecycle, from problem framing to deployment, while shaping the future of our lending strategy.

The role offers hybrid work, with two days per week in our Central Birmingham office, and the flexibility to work remotely most of the week, collaborating closely with Data and Risk teams.

Qualifications

• Strong experience in machine learning within lending (SME lending essential)
• Strong consumer lending experience
• Proficiency in Python and SQL
• Proven end-to-end model development experience
• Background in fintech and automated decisioning environments
• Solid understanding of UK credit risk and regulation
• Experience with model governance and monitoring frameworks
• Ability to communicate effectively with both technical and business stakeholders
• Strong commercial mindset and ownership attitude

Responsibilities

• Build and deploy ML and statistical models for credit risk, affordability, and pricing
• Own the full model lifecycle, including data, feature engineering, modelling, validation, deployment and monitoring
• Develop monitoring frameworks and performance dashboards
• Drive innovation through new data sources, challenger models and experimentation (A/B testing)
• Translate complex models into clear, actionable business insights
• Work closely with Data and Risk teams to influence lending strategy and decision-making

Skills

Python

SQL

Machine Learning

Credit risk

A/B testing

Job description

Lovey in the UK is seeking a Senior Decision Scientist to lead the development of credit decisioning models across SME lending. You will own the end-to-end model lifecycle, from problem framing to deployment, while shaping the future of our lending strategy.

The role offers hybrid work, with two days per week in our Central Birmingham office, and the flexibility to work remotely most of the week, collaborating closely with Data and Risk teams.