Role Overview:

Develop statistical models, risk scorecards and predictive solutions to generate business insights and support data-driven decision-making.

Key Responsibilities:

- Extract, clean, transform and analyse data from multiple sources.

- Conduct statistical analysis, data mining and deep-dive business analysis to identify trends, risk segments and business drivers.

- Develop and validate acquisition and behavioural scorecards, predictive models and machine learning solutions.

- Apply statistical techniques to solve business problems and generate actionable insights.

- Implement models in scoring processes and refine them based on performance feedback.

- Analyse opportunities across risk, portfolio, finance, customer behaviour, cross-selling and retention.

- Collaborate with business and technology teams to gather requirements and resolve data or implementation issues.

- Present modelling outcomes and recommendations to stakeholders.

Technical Skills :

- Strong proficiency in Python, R, Excel and statistical modelling.

- Experience in regression, logistic regression, time-series forecasting, clustering, decision trees, CART/CHAID, hypothesis testing, survival analysis, factor analysis and optimisation techniques.

- Hands-on experience in risk scorecards, predictive modelling, machine learning and model validation.

- Strong SQL/database knowledge and data preparation skills.

Qualification :

- Graduate/Postgraduate in Statistics, Mathematics, Economics, Data Analytics or Operations Research.