Led a team of six in developing sophisticated retail loan default prediction and propensity-to-pay models, significantly enhancing the company's risk assessment and decision-making capabilities. The ML model we designed effectively detected fraudulent activity, potentially reducing NPA by up to 20%, and collection efficiency by 25%.Led a team of three in developing a versatile Data-Driven Decision system that empowers companies to make well-informed decisions by analyzing historical data trends and causal impacts. Designed and implemented interpretable classification, KPI forecasting, and regression modules adaptable to various use cases, resulting in onboarding multiple clients.Unearthed insights from financials, revealing successes, risks, and gaps, and predicted key focus areas to boost revenue by considering causal impacts. This analysis helped to raise money from private equity.Pioneered the development of an advanced ML-based Crop Yield Prediction module, elevating prediction accuracy by nearly 10%. This breakthrough led to substantial cost savings through reduced stockouts and minimised discount sales. Created and deployed an innovative Employee Attrition Prediction module, empowering early detection of attrition trends up to three months in advance. Utilised data-driven strategies to curtail attrition among top talent, achieving an impressive 10-30% increase in early attrition detection.Created an NLP engine that extracts actionable insights from feedback, reducing data processing time from months to days. Used unsupervised algorithms to consolidate similar feedback and enable category-based drill-down analysisImplemented a Self-Service Chatbot streamlining HR issue resolution, reducing HR effort by 30-40% and enhancing overall efficiency.Currently, I'm spearheading a team of 12 engineers tasked with developing reusable GenAI assets for our company.