Mar 2025 – Aug 2025 · 5 mos · Bengaluru, Karnataka, India · On-site

• As Head of the Consumer Model Development Centre (India), I lead teams advancing deposit growth, lending acquisition, and retail process efficiency through advanced analytics and GenAI. Our GenAI Pod is at the forefront of this transformation, deploying solutions like an in-house RAG chatbot for branch support, using LLMs to process and summarize over 70,000 employee ideas, and deploying AI agents to analyze 3,000+ daily call transcripts for actionable insights and compliance. Beyond GenAI, my teams leverage quantitative models to optimize branch network strategy and staffing, and build sophisticated classification and causal inference frameworks for hyper-targeted marketing and robust impact measurement.

Jan 2022 – Feb 2025 · 3 yrs 1 mo · Greater Delhi Area · On-site

• At Resilient AI, we were revolutionizing India's small credit landscape (loans < ₹50K) with $3M in seed funding, inspired by Upstart's AI-driven model. Our core innovation was a sophisticated income and default prediction model using a blend of traditional data (credit scores, income) and non-traditional metrics (education, assets, work history) to accurately assess repayment capacity. We built a full-stack solution—encompassing LOS, LMS, CRM, and CMS—that empowered NBFCs to process over 100K+ applications daily. This system enabled our partners to make efficient lending decisions, minimize risk (NPA < 3.5%), and achieve high revenues (12%+ ROA), making small credit a viable and attractive market.

Apr 2015 – Dec 2021 · 6 yrs 8 mos · Hyderabad/ Bangalore / Gurgaon - India · On-site

• As Director, ML Strategy for Global Product Assurance Risk and Safety team, I led a product roadmap that significantly elevated safety across Amazon's vast international selection. At the helm of a diverse, 70+ member team spanning India, US, and EU - comprising Scientists, Product Managers, UI/UX Designers, and Data Engineers - my leadership fostered collaboration and delivered results-driven solutions that safeguarded customers and sellers alike while upholding Amazon's stringent global product safety standards.
• In my second stint as Senior Manager, ML strategy at Amazon India Retail Business, I led the delivery of an advanced ML roadmap that drove improvements in multiple areas. This included a 20% reduction in returns to origin through targeted ML-based interventions aimed at improving payment on delivery experiences, and a 90%+ reduction in fake or incomplete addresses by prompting customers to correct zip codes or add missing address components. Additionally, the roadmap improved payment success rates through optimal ML-driven payment processor selection and developed personalized recommendations for building grocery baskets. At the helm of this high-performing team of 30+ scientists, I fostered an environment that encouraged collaboration, creativity, and innovation in delivering cutting-edge ML solutions, ultimately leading to my promotion to Director, ML Strategy.
• I started my Amazon journey as Senior Manager, Capacity Planning, where I led the creation of the Center of Excellence (CoE) for Planning from scratch to a team of over 100 employees. The CoE executed Amazon's worldwide (WW) customer service staffing plan through forecasting and capacity alignment across geographies, ensuring seamless delivery of service levels of customer service. Under my leadership, the high-performing team collaborated with WW stakeholders to drive improvements across the planning process and transformed the CoE into a critical component of customer service operations.

Sep 2014 – Apr 2015 · 7 mos · Gurgaon, India / Johannesburg, South Africa / Delaware, United States · On-site

• As AVP Risk Management, I was part of two impactful assignments that yielded significant results. In the first assignment with a large US bank, we delivered recommendations on receivables placement and timely litigation, leading to $50M+ improvement in collections. The second assignment with a large South African bank involved cost structure rationalization, resulting in $100M+ savings through employee rationalisation, technology optimization, and other efficiency measures. Additionally, I drove collaboration between consulting teams and technical stakeholders to build business intelligence products while spearheading project staffing and recruitment efforts within the firm, ensuring seamless execution of critical projects.

Jan 2006 – Sep 2014 · 8 yrs 8 mos · Gurgaon, India / New York, United States · On-site

• In my last role as Director of Institutional Risk, I led the development and execution of cutting-edge risk decision infrastructure across two critical business units: Global Corporate Card and Global Merchant Services. At the helm of a high-performing team of 25+ data scientists, I spearheaded strategic initiatives that informed risk assessment and mitigation decisions, ensuring seamless alignment with risk provision goals.
• As Director, Small Business Credit Risk, I led Amex's small business credit card portfolio - the largest in the US by account receivables and number of served businesses. As leader of the Credit Risk Decision science team, I drove a team of 20+ data scientists to craft innovative machine learning (ML) scorecards and frameworks that accurately mitigated credit loss risks. These strategic initiatives delivered optimized portfolio credit risk performance, positioning Amex for continued success.
• As Senior Data Scientist, Global Risk Oversight, I led the review of systemic risk threats, assessing their potential impact on Amex's consumer credit card portfolio. I developed early warning metrics to identify emerging risks, collaborating with business risk teams to address major credit performance volatility. My efforts drove strategic decisions that optimized portfolio stability and minimized potential losses.
• As Senior Data Scientist, Consumer Credit Risk, I developed machine learning models across the customer life cycle - New account underwriting, credit risk management, fraud prevention, collections, customer retention, and customer acquisition. My expertise in ML model development enabled Amex to make data-driven decisions that drove business growth and minimized potential losses.

Jun 2004 – Dec 2005 · 1 yr 6 mos · Bengaluru Area, India

• I played a key role in supporting HSBC's acquisition strategy for its US private label credit card portfolio. My primary responsibilities included developing statistical models to identify high-value customers, delivering data-driven campaign performance analytics, and crafting targeted strategies with tailored treatments to drive business growth. Additionally, I trained new team members as we transitioned work from the Chicago-based in-market team, ensuring a seamless handover of critical initiatives.