Credit Risk Data Scientist - Hybrid (London)

iwoca

Greater London

Hybrid

GBP 60,000 - 80,000

Full time

14 days+

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Benefits offered by this job

Flexible working hours
Medical insurance
Private GP service
Sabbatical after 4 years
25 days holiday + birthday

Job summary

iwoca is seeking a Data Scientist for its iwocaPay Risk Squad in London. You will co-own credit models and shape risk modelling development, focusing on supervised ML on tabular data and data engineering as the squad builds its pipelines.

You’ll contribute to model decisions, collaborate with product and strategy teams, and drive testing of ideas across related lending data science groups. A hybrid office pattern supports flexible work and growth.

Qualifications

  • Background in probability and statistics from a quantitative field.
  • End-to-end supervised ML on tabular data (exploration, training, deployment, monitoring).
  • Ability to work in a small, early-stage team with loosely defined problems.
  • Judgement to know when a model is ready to go live and how to explain it.
  • Experience using AI to augment modelling work and tooling.
  • Clear written and spoken communication for non-technical colleagues.

Responsibilities

  • Co-own credit models with another data scientist and review work.
  • Build supervised ML on tabular data and data pipelines.
  • Lead model development from automated credit to invoice financing models.
  • Collaborate with iwocaPay product and strategy meetings.
  • Prototype ideas and test with other data science teams.

Skills

Statistics
Production ML
Ownership
Model evaluation
Communication
AI leverage
Python

Tools

Python

Job description

iwoca is seeking a Data Scientist for its iwocaPay Risk Squad in London. You will co-own credit models and shape risk modelling development, focusing on supervised ML on tabular data and data engineering as the squad builds its pipelines.

You’ll contribute to model decisions, collaborate with product and strategy teams, and drive testing of ideas across related lending data science groups. A hybrid office pattern supports flexible work and growth.

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