Lead Decision Scientist, Lemfi

• You are a candidate who would thrive in a fintech startup environment like ours, where we readily accept individuals with a humble, yet uplifting attitude alongside a diligent sense of work ethic
• The teams here at LemFi are passionate about their work and fields of expertise, but also lend hands on cross-functional responsibilities to ensure the success of the company and the satisfaction of our clientele
• 5-7 years of experience in consumer credit, particularly in a data science or decision science role
• Hands-on experience building models in Python using libraries like scikit-learn, XGBoost, or LightGBM
• Strong experience working with transactional datasets (e.g., Open Banking and Categorisation) and bureau data (e.g., Experian, Equifax)
• Deep understanding of feature engineering, data preprocessing, and dealing with class imbalance
• Ability to evaluate models using appropriate metrics (e.g., AUC, KS, precision/recall) and validate across multiple segments
• Familiarity with standard practices around model monitoring, performance tracking, and data drift
• Strong SQL skills for data extraction, joining, and transformation

Desirable

• We’re seeking a highly analytical and detail-oriented Lead Decision Scientist to own the development, deployment, and optimisation of credit decisioning and risk models
• You will play a central role in shaping our lending strategy, building data products, and driving portfolio performance through data-led insight
• This role is ideal for someone with strong analytical and technical skills who thrives on data exploration, modeling, and experimentation
• Lead the development and maintenance of credit risk and affordability models using bureau, open banking, and alternative behavioural data
• Own end-to-end model lifecycle: data sourcing, feature engineering, model development, validation, and monitoring
• Design and execute champion/challenger tests and A/B experiments to continuously improve approval rates, loss rates, and customer experience
• Analyse credit performance data to generate actionable insight and support strategic decisions
• Mentor and develop a small team of analysts/data scientists as the team scales
• Work closely with Data Engineering to deploy models into production pipelines
• Collaborate with stakeholders to define modeling goals and interpret model outcomes in a business context