Data Scientist (Mid and Senior Level) (Consumer Credit)

Location: London, United Kingdom; hybrid attendance at the London office 2–3 days per week. Working from abroad is available for up to 120 days per year, subject to having the right to work in the chosen country.

Company

hirify.global is a digital bank focused on consumer lending and credit products.

What you will do

• Take ambiguous credit-related questions from stakeholder discussions through to practical modelling and analysis.
• Build, improve, and maintain models supporting consumer-credit decisions.
• Develop flagship risk models and value-driver models covering revenue, profit prediction, and customer lifetime value.
• Use Python and statistical judgement to develop classification and regression solutions.
• Partner with Credit Strategy, Product, and Engineering to prioritise work and support productionisation.
• Explain technical choices, build consensus, and own delivery in a collaborative environment.

Requirements

• Hands-on data science experience with practical Python and Git capability.
• Knowledge of statistical-learning models and machine-learning algorithms for classification and regression.
• Strong statistical fundamentals, including hypothesis testing and experimental design.
• Ability to independently take ambiguous problems from discussion to a useful model or analysis.
• Clear communication with technical and non-technical stakeholders and effective collaboration across business, Product, and Engineering.
• Right to work in the country where work from abroad is performed.

Nice to have

• Experience in consumer credit, lending, credit cards, or a related credit-risk domain.
• Exposure to sequence-based deep-learning or transformer-style models.
• Experience building production-grade Python microservices.

Culture & Benefits

• Flexible hybrid working with face-to-face collaboration.
• Work-life balance support and resources for working effectively from home and the office.
• Option to work from abroad for up to 120 days per year, subject to local right-to-work requirements.
• Collaborative, low-ego environment with meaningful individual ownership.
• Inclusive workplace with a diversity, equity, and inclusion forum and support for reasonable adjustments.

Hiring process

• Mid- and senior-level candidates are assessed according to experience, technical depth, and scope of impact.
• Behavioural and competency-based interviews must be completed without AI assistance.
• AI use in technical interviews depends on the role and is clarified by the Talent Partner.