Overview
As a Senior Data Scientist in the Credit Risk Modelling team, you will steer the technical direction of multi-quarter projects that shape how credit risk is assessed at iwoca. You’ll work within a ~12-strong data science team to own end-to-end modelling initiatives, balancing production health with new research. The role blends rapid iteration, deployment, and strategic R&D to push the boundaries of how models inform pricing and portfolio decisions. You’ll collaborate across teams to unlock value from advanced analytics while advancing the company mission to support more SMEs. This is a high-impact role for someone who thrives on data-driven decision making and scalable, interpretable models
Pay / Benefits
- Flexible working hours
- Medical insurance from Vitality with gym discount
- Private GP service for you and dependents
- 25 days’ holiday + birthday leave + buy/sell extra days
- 1-month fully paid sabbatical after four years
- Pension contributions (3%) and equity scheme
Responsibilities
- Own credit and CLtV modelling projects end to end, from opportunity spotting to commercial impact
- Maintain production models, guide incremental development, and lead research initiatives
- Prototype and deploy AI/ML solutions to enable faster experimentation and deployment
- Unify auto and manual models and design principled cost functions for a common framework
- Contribute to IFRS accounting model and other multi-stage modelling efforts
- Evaluate model outputs critically and defend reasoning under scrutiny
- Lead project work and communicate findings to technical and non-technical audiences
Key requirements
- Background in probability and statistics from a quantitative field
- Experience building and shipping supervised ML models end to end (exploration, training, deployment, monitoring)
- Proactive research mindset with ability to drive value through experimentation
- Strong judgement for evaluating model outputs and explaining decisions
- Proven project leadership for modelling initiatives from framing to landing commercial impact
- Proficiency in AI as a primary tool and ability to prototype and automate with it
- Clear communication tailored to the audience
- Strong judgement under challenge and evidence-based reasoning
- Collaborative and cross-functional mindset
- Python
- Production ML
- Gradient boosting or neural networks on tabular data (production)
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