Data Scientist

Gravitas Group; Crewe; On-site; GBP 50,000 - 60,000; Full time

Benefits offered by this job

Competitive salary and bonus scheme

Comprehensive benefits package

Autonomy and ownership

Job summary

Gravitas Group in Crewe is seeking a Data Scientist (Credit Risk) to design and deploy credit risk models across the customer lifecycle. You will work with Credit, Finance, Commercial and Analytics stakeholders to translate business challenges into scalable data science solutions.

The role offers autonomy, exposure to senior stakeholders, and a modern analytics environment. Candidates should have 3+ years in data science or credit risk modelling, strong Python/SQL, and proven ability to build

Qualifications

• 3+ years' experience in Data Science, Credit Risk Modelling, Quantitative Analytics, or similar.
• Proven experience building and validating predictive models in a commercial environment.
• Strong Python and SQL skills.

Responsibilities

• Design, develop, validate, and maintain credit risk models across the customer lifecycle.
• Build and validate application scorecards, behavioural scorecards, and recovery models.
• Apply modern ML/statistical techniques including gradient boosting and survival analysis.
• Translate business challenges into structured modelling problems and deliver actionable insights.
• Develop monitoring frameworks to track model performance and stability.
• Present findings clearly to technical and non-technical stakeholders.

Skills

Python

SQL

Credit risk modelling

Predictive modelling

Job description

Data Scientist (Credit Risk)

Location: Crewe (on-site) Salary: £50k - £60k + 10% Bonus + Benefits

Gravitas are delighted to be exclusively partnering with a market-leading global technology and mobility organisation to recruit a Data Scientist (Credit Risk).

This is a unique opportunity to join a high-growth business that is investing heavily in data and analytics. You'll play a pivotal role in designing and deploying predictive models that sit at the heart of the company's credit decisioning process, directly influencing commercial outcomes and risk strategy.

If you're passionate about turning complex data into actionable insights and enjoy building models that drive real-world decisions, we'd love to hear from you.

The Opportunity

As a Data Scientist within the Credit team, you'll be responsible for the end-to-end development, validation, and monitoring of credit risk models across the customer lifecycle. Working closely with senior stakeholders across Credit, Finance, Commercial, and Analytics, you'll translate business challenges into data science solutions that drive smarter lending and credit decisions.

This is a highly visible role offering significant autonomy, ownership, and the opportunity to shape the future direction of credit modelling within a rapidly evolving business.

Key Responsibilities

• Design, develop, validate, and maintain credit risk models, including:
  • Application scorecards
  • Behavioural scorecards
  • Recovery propensity models
  • Customer lifetime value models
• Apply modern machine learning and statistical techniques including gradient boosting, classification, regression, and survival analysis.
• Translate commercial and credit risk challenges into structured modelling problems.
• Build robust monitoring frameworks to track model performance and stability over time.
• Assess model effectiveness using measures such as Gini, CAP, population stability, and other relevant performance metrics.
• Work directly with complex, real-world datasets from multiple source systems to prepare model-ready data.
• Support and contribute to broader data modelling and data engineering activities within the Credit function.
• Present findings and model outputs clearly to both technical and non-technical stakeholders.
• Ensure methodologies, assumptions, and outputs are fully documented and governed.

About You

We're looking for a hands-on Data Scientist with a strong quantitative mindset and a genuine interest in credit risk and predictive modelling.

Essential Skills & Experience

• 3+ years' experience in a Data Science, Credit Risk Modelling, Quantitative Analytics, or similar role.
• Proven experience building and validating predictive models in a commercial environment.
• Strong Python and SQL skills.
• Experience working across classification and regression modelling techniques.
• Practical experience handling large, complex datasets from multiple sources.
• Strong stakeholder engagement and communication skills.
• Ability to explain complex modelling concepts and limitations to business audiences.

Desirable Experience

• Credit risk, lending, financial services, banking, fintech, or related domain experience.
• Experience with survival analysis.
• Knowledge of model governance, monitoring, and validation frameworks.
• Experience developing scorecards or decisioning models.

Why Apply?

This is an opportunity to join an ambitious, innovative organisation that is continuing to invest in technology, sustainability, and data-driven decision making.

You'll benefit from:

• Competitive salary and bonus scheme
• Genuine autonomy and ownership
• Opportunity to shape a growing Data Science capability
• Exposure to senior stakeholders and strategic initiatives
• Modern technology and advanced analytics environment
• Strong focus on innovation and continuous improvement
• Inclusive and supportive company culture
• Comprehensive benefits package

Diversity & Inclusion

Our client is committed to building a diverse and inclusive workplace where everyone can thrive. Applications are welcomed from all backgrounds, and reasonable adjustments are available throughout the recruitment process.