Greater Sydney Area
A data science, modelling, credit, funding and analytics professional with experience in: Credit Risk Scorecards ML Lending Models AI use in ML AI use in Lending Behavioural Scorecards IRB Modelling IFRS9/AASB9 Modelling Causal Inference and Cohort Design Behavioural and risk-based pricing models Agentic Workflows Credit Strategy and Valuations App-based lending Marketing/ Pricing Campaign Design and Evaluation Optimization Data and ML Products Product Analytics Customer Analytics Key points of technical differentiation: Quantitative Market Risk/ Investment Risk Securitization Financial Modelling Investment Analytics Strong financial background (from historical investment work) Core strengths in fintech lending in developed and emerging markets Key personal strengths: Explaining technical outputs to non-technical stakeholders (incl Board and Exec) Exceptionally commercially minded with a CFA Chartership Growing and managing teams Strong Communicator and coalition builder
Running the APAC Data Science function at Tilt with a core focus on lending in emerging markets such as India and the Philippines.
Responsible for creating and advancing the data science and advanced analytic capabilities of Pepper through the building of statistical/ ML models and applications, Generative AI solutions and quantitative analysis to credit, pricing, collections, sales, credit risk, executive and Treasury
Solving a variety of problems across the global Pepper business: predictive analytics in loss forecasting and credit delinquency; designing interest rate framework and hedging for IRRBB; building and deploying ML models.
Validating and parameterising the new valuation and market risk model.
Building IFR9 projection ML models for both book time series and individual loan classification.
1 month contract building cashflow forecasts and discount curves.