Moniepoint - Senior Data Scientist (Credit)

• Develop and deploy credit scoring, affordability, and behavioural models to support underwriting, pricing, and collections • Design and run experiments to optimise approval rates, loss rates, and profitability • Partner with product squads to embed decision logic into real-time systems • Ensure data quality, compliance, and ethical use of models across all decisioning processes • Mentor product squads on best practices in experimentation and data-driven decision-making • Provide models to optimise outcomes in collections, churn management and user retention • We would love to hear from you if… • You’re comfortable with Statistics and have a Degree or qualifications  in a quantitative field (Statistics, Mathematics, Engineering or similar) • You have +5 years of experience in data science, decision science, or risk analytics within financial services • Working knowledge of credit risk, consumer lending, and regulatory considerations • Proficiency in SQL and at least one modelling/programming language (Python, R) • Experience with A/B testing, machine learning, collections modelling and churn management • Ability to translate complex analyses into clear recommendations for business stakeholders • High ownership mindset and comfort working in fast-paced, cross-functional teams • What we can offer you • Culture: We put our people first and prioritise the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human. • Learning: We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks. • Compensation: You’ll receive an attractive salary, pension, health insurance, monthly bonuses, plus other benefits • What to expect in the hiring process • A preliminary phone call with the recruiter • A coding exercise on HackerRank - covering core data science theory (math, statistics, linear algebra) and Python fundamentals (data structures & algorithms). • A take-home assignment • A technical interview with a Lead in our Data Science Team to review your take-home assignment in depth • A behavioural and technical interview with the hiring manager