Credit Risk Data Scientist - Harnham - Data & Analytics Recruitment : Job Details

DATA SCIENTIST (CREDIT RISK)

UP TO £70,000

LONDON

This is a new opportunity to sit in this companies core analytic function, where you will hold responsibility for all things data related. You will drive the direction and scope of data science within the team and company.

THE COMPANY

This is an exciting business who provide motor loans for dealer and broker partners. They are using cutting-edge technology and data to improve their services and offerings.

THE ROLE

You will be doing the following daily:

• Apply data science and machine learning methods for prediction, automation, and behavioural analysis.
• Develop new behavioural scorecards, collection scorecards, and loss forecasting scorecards.
• Conduct analyses to support and identify new projects, products, and business opportunities, presenting findings and recommendations to senior management.
• Manage the model validation and review process.
• Proactively discover areas where analytics can provide value through insights or automation.
• Serve as an internal consultant, interpreting user requests and suggesting improved or alternative solutions to achieve desired outcomes.
• Continuously explore and evaluate new tools and techniques for analysis, modelling, data exploration, and presentation, implementing them as appropriate.
• Regularly use Python, SQL, and Excel.
• Assist in documenting core processes and procedures.
• Opportunity to learn and adopt additional tools and languages as the team's and business's needs evolve.

YOUR SKILLS AND EXPERIENCE

• Knowledge of Machine Learning algorithms.
• Strong proficiency in Python.
• Previous experience deploying models into production.
• Knowledge of scorecard building.
• Proficiency in SQL.
• Strong numerate degree from a Russel Group University.
• Excellent written and verbal communication skills.
• Desire to work in a fast-growing and fast-paced environment.

THE BENEFITS

• Up to £70,000 salary.
• Discretionary bonus.
• Pension scheme.
• Hybrid working model.

HOW TO APPLY

Please register your interest by sending your CV to Gaby Adamis via the Apply link on this page.