Luxembourg
I’m an applied machine learning leader with 10+ years of experience building ML and AI-driven products across e-commerce, banking, and operations. Currently, I lead a multidisciplinary team of ML scientists, engineers, and product managers at Amazon, where we develop ML solutions using multi-modal data (thermography, ultrasonic, and sensor streams) to keep amazon machine running at a global network of 1,000+ warehouses. In my previous roles at Amazon, my team delivered ML products for customer service and books businesses. My work sits at the intersection of machine learning, product, and operations. I focus on translating complex data into production-grade systems that deliver measurable business impact—whether it’s predicting equipment failures, detecting fraud, or improving customer experience through NLP-driven insights. Previously, I led data science and analytics teams tackling high-impact problems such as fraud detection, abuse prevention, contact prediction, and defect detection. I’ve built and deployed end-to-end ML systems covering churn, LTV, propensity modeling, and experimentation frameworks, as well as scalable data and ML infrastructure. Before Amazon, I established analytics capabilities in financial crime at Axis Bank, leading initiatives in fraud detection, anti-money laundering, and credit risk, and deploying ML systems to modernize legacy processes. I also bring experience from Goldman Sachs and Standard Chartered, where I worked on data-driven solutions in banking and marketing analytics. I’m passionate about building high-performing teams, create organization wide impact, owning problems end-to-end, and applying machine learning to solve real-world challenges at scale.
I lead a high-performing team of ML Scientists, Engineers, and Product Managers dedicated to redefining predictive maintenance. By leveraging multi-modal data—from thermography to ultrasonic sensors—we build ML products to predict failures before they happen and transform global operations across 1,000+ warehouses worldwide, delivering measurable impact through end-to-end ML & product ownership.
I am leading a team of Data Scientists and Business Intelligence Engineers to deliver ML and Analytics solutions. My team and I use NLP on customer-agent conversation data to build AI solutions for multiple problems such as contact prediction, fraud detection, abuse prevention, defect detection etc.
In this role I worked as a Senior Data Scientist and delivered multiple projects for digital reading business. Few key projects are below - 1. Fraud detection models 2. Marketing Models - Churn, LTV, Propensity, Revenue Growth, A/B Testing 3. End to end data and ML ops infra to enable analytics and ML
I was leading Data Science and Analytics initiatives for Banking Fraud, Money laundering, Digital lending and Credit Risk areas for the bank. I set up analytics practice in financial crime in the bank from scratch and introduced ML based systems to replace old systems. I also led efforts and delivered multiple ML solutions to identify fraud and money laundering activities during 2016 Indian banknote demonetization.
- Marketing Analytics - Product Analytics - Campaign Management - Customer Life Cycle management
- Worked on process efficiency enhancement for the payroll department - This eventually helped in acquiring new clients without increasing manpower