Company: Liberis
Location: London
Job Description:
Overview
In this role you will design and optimise global decisioning and pricing strategies to balance risk, commercial value and customer outcomes. You will work within the Risk function, collaborating with Product and Commercial teams to unlock value and support rapid growth. You will explore data sources, monitor auto-decisioning rules and predictive models, and contribute to the life cycle of machine learning solutions. This position offers cross-functional impact across risk, analytics and pricing, with a mission-driven focus on enabling digital lending at scale. You will join a hybrid team culture that values collaboration, technical excellence and pragmatic decision making.
Pay / Benefits
- hybrid working
- office 3–4 days a week
- flexibility as a core culture
Responsibilities
- Lead development and optimisation of global decisioning strategies
- Shape pricing policy balancing risk, value and customer outcomes
- Drive positive business impact by expanding customer reach within risk appetite
- Explore new and existing data sources to improve decisioning and pricing
- Collaborate with risk stakeholders to maintain acceptable risk levels in a dynamic environment
- Represent Risk to the wider business and unlock value with Product and Commercial teams
- Work with the Machine Learning team on the lifecycle of predictive models and feature proposals
- Own and enhance monitoring of auto-decisioning rules and predictive models
Key requirements
- 2-4 years of analytical experience
- Strong ability to turn data into insights and communicate findings clearly
- Proactive, autonomous work style with attention to detail
- Experience or interest in machine learning models
- Proficiency in SQL
- Strong MS Excel skills
- GCP experience and Python skills are a plus
- Experience with data visualization tools such as PowerBI or Looker
- STEM background valued; aptitude emphasized over formal education
- clear communication
- proactive initiative
- attention to detail
- SQL
- MS Excel
- Python
…
Posted: September 14th, 2026