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# Senior Data Scientist

- **Company:** Harnham
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £60,000.0 - £80,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Python (Programming Language), Machine Learning, Standard Sql, SQL Databases, Build Management, Data Management, Machine Learning Operations
- **Published:** October 30, 2026
- **Apply:** https://www.reed.co.uk/jobs/senior-data-scientist/57506219

## About the Role

* Strong commercial experience in Data Science within credit risk, lending, or financial services.
 * Experience building predictive credit models from scratch.
 * Hands-on machine learning experience in a commercial environment.
 * Strong Python and SQL skills.
 * Experience developing credit scorecards, risk models, or forecasting models.
 * Ability to communicate technical concepts effectively to stakeholders.
 * Experience working with consumer lending or SME lending portfolios would be beneficial., * Analytical Thinking (Solving)
 * Communication Skills (Key)
 * Data Analysis (Administration)
 * Data Science (Master)
 * Machine Learning
 * Mathematics Knowledge
 * Python Programming (Beginner)
 * SQL Databases
 * Stakeholder Management (Business)
 * Statistical Knowledge

## Description

This Senior Data Scientist role offers the chance to work on end-to-end credit risk modelling within a highly data-driven environment where analytics is central to commercial success.
THE COMPANY
This growing financial technology business uses advanced analytics, machine learning, and automated decisioning to deliver funding solutions at scale. Operating across multiple markets, they have built a strong reputation for innovation and continue to invest heavily in their data capabilities. Their Data Science team works closely with Risk, Engineering, and Product functions to drive business growth through data-led decision making.
THE ROLE

 * Build and deploy credit risk models from scratch, including scorecards, probability of default models, and forecasting models.
 * Apply machine learning techniques to improve underwriting and risk assessment processes.
 * Analyse large and complex datasets to identify trends, opportunities, and risks.
 * Develop predictive models to support business performance and customer outcomes.
 * Collaborate with Product, Engineering, Credit Strategy, and Risk teams to deliver data-driven solutions.
 * Create visualisations and communicate analytical findings to technical and non-technical stakeholders.
 * Support model deployment, monitoring, and best practice model lifecycle management.
 * Contribute to the ongoing development of the organisation's data science capability.