Data Scientist

1. Leveraged Salesforce Einstein to implement predictive modelling solutions, including opportunity scoring, and customer churn prediction, enabling proactive customer engagement and optimized resource allocation. 2. Created CRM analytics and Tableau reports and dashboards to monitor key sales metrics, including lead conversion rates, sales pipeline velocity, average deal size, and customer acquisition costs, thereby enhancing decision-making processes. 3. Managed ETL processes, including data migration from Salesforce to Microsoft Fabric, improving data integrity between Salesforce and external databases and achieving a 36% reduction in manual labour hours. 4. Implemented responsive web solutions to enhance user experience using JavaScript, Apex, and Visualforce.

1. Led a team to develop multiple credit risk models leveraging predictive modelling and analytics for underwriting digital loan applications, reducing default rate by 15% for SME lending and approximately 23% for retail lending. 2. Enhanced credit portfolio management strategies through comprehensive data analysis, such as vintage analysis, leading to better loan affordability calculations. 3. Income and expense estimation for salaried and non-salaried customers based on BERT and cosine similarity classification of bank transactions, resulting in better loan affordability calculations. 4. Developed KYC verification model leveraging one-shot learning for speaker verification, reducing fraud incidents by 9%.

1. Developed new and behavioural credit risk scorecards for retail loans, achieving a 4% default rate in the low-risk bucket. 2. Implemented collections prioritisation models, improving collections strategies based on customer segmentation. 3. Developed KPI dashboards in Tableau and Looker for real-time product and transaction monitoring, tracking key metrics such as month-on-month attrition, transaction volume and speed, customer lifetime value (CLTV) model, and conducting vintage analysis. 4. Implemented customer lifetime value model (CLTV) to identify high-value customers, driving monthly loan disbursements to USD 4.5M and improving default rates.