Headline

VP / Head of AI Products | ML Models & Agentic AI in Regulated BFSI | Insurance + Supply Chain AI | Data Scientist turned Product Leader | Ex-Prudential, Resilinc

About

Currently serving as Vice President, AI & Data Science Products at Kotak Life Insurance, leading the AI product charter, applied data science organisation, and model governance agenda across underwriting, pricing, distribution, and sales enablement. My focus is on moving a regulated insurer from passive predictive scoring to agentic decisioning — multi-agent underwriting , multi-model sales copilots deployed across the tied agency network, and alternate-data pricing on FIG book ,building systems that are simultaneously cheaper per decision and defensible to regulator. Previously, I built and commercialised AI products at Resilinc, a supply chain risk intelligence company, joining as an early employee and contributing through Series B. I originated Autonomous Supplier Mapping from whitespace to a standalone revenue line, architected on a graph database because the underlying problem was relational rather than predictive, and shipped CommodityWatch, a patent-pending commodity forecasting engine, alongside a RAG-based GenAI insight assistant for enterprise risk teams. Operating at the intersection of 0→1 product discovery and enterprise deployment, I carried these products through market sizing, pricing, and adoption across a global enterprise account base, including engagement with the U.S. Department of Defense. My foundational leadership experience spans eight years at Prudential across Singapore and Mumbai, where I owned the regional AI Centre of Excellence across five APAC markets and directed data science teams across claims automation, dynamic pricing, lapse prediction, and FCA-grade voice compliance systems. I am a strong proponent of translating between technical and commercial audiences, with a decade of hands-on machine learning practice underpinning four years of AI product leadership ,experience built across insurance, supply chain, and financial services, and across environments ranging from Series B startups to global enterprises.

Location

Bengaluru

AI stack

claude code

elevenlabs

hermes agent

hugging face

langgraph

langsmith

Work experience

VP of AI Products at Kotak Life, Apr 2025 - Present · 1 yr 8 mos, Bengaluru, Karnataka, India, Leading Kotak Life’s AI transformation across underwriting, claims, distribution, and customer engagement. Driving enterprise-grade AI platforms to accelerate automation, improve decision quality, and boost frontline productivity. Partnering with the Chief Data Officer to scale AI from experimentation to production and embed intelligence across the organization. KEY HIGHLIGHTS - AI Transformation Charter: Defined a multi-year AI roadmap, aligning product, data, and business strategy across the enterprise. - Underwriting Automation (Agentic AI): Leading deployment of an AI platform that automates proposal intake, financial and medical risk evaluation, and decision-making. Projected to handle up to 90% of routine scrutiny and underwriting checks, freeing underwriters for complex cases. Establishes a foundation for scalable, real-time AI underwriting across all channels. - Group Insurance Pricing (Alternate Data): Leading development of an ML pricing model on a ₹1,200 Cr group book, using alternate data signals the industry does not traditionally price on, to optimise discounting on risk rather than on negotiation. - Rewards & Recognition Optimizer: Built an allocation product that optimises a ~$1M incentive budget across 100K+ agents. Models product mix and agent personas by channel to identify where reward spend produces genuine behaviour change versus where it pays for performance that would have happened anyway, then reallocates from low-yield segments into high-yield ones. - Sales AI Assistant (Agentic AI): A multi-model GenAI assistant deployed across the tied agency network, guiding agents through product recommendation, objection handling and query resolution. Drove a 30% lift in sales efficiency Scope: Leading 14+ data scientists, product managers, and engineers; collaborating with C-suite stakeholders across product, risk, and distribution to align AI initiatives with enterprise strategy.

Senior Product Manager AI at Intent HQ | AI Company of the Year, Nov 2024 - Mar 2025 · 5 mos, London Area, United Kingdom, • Successfully defined the vision, scope, and unique value proposition of the Large Behavioral Intelligence Platform product, aligning with market needs and business goals • Delivered-in-depth total addressable market analysis to strategically define market opportunities and align product positioning with business growth objectives

AI Product Manager at Resilinc, Jan 2023 - Nov 2024 · 1 yr 11 mos, London Area, United Kingdom, Transitioned into AI Product Management, reporting to AVP, enabling me to enhance my business acumen and drive impactful AI-driven product solutions. Led cross-functional teams to build innovative AI products that optimized customer experience and supply chain visibility. • LLM-Powered AI Assistant: Led the development of a Gen AI RAG-powered chatbot using Large Language Models (LLMs), enabling customers to quickly access valuable insights through an intuitive, AI-powered product analytics interface. Additionally, developed a two-year product roadmap to expand and evolve the assistant’s capabilities, ensuring long-term value and scalability • Recommendation Engine for Sub-Tier Visibility: Designed and spearheaded the development of graph-based AI models to optimize supplier mapping, enhancing visibility and decision-making in supply chain management • Business Case & Roadmap Development: Built the foundational business case for AI product initiatives, contributed to product roadmap development, and interviewed customers for requirement gathering, ensuring solutions aligned with user needs • Risk Score Ideation: Led the ideation and creation of new risk scores to further enhance product decision-making and risk management capabilities Key Skills: AI Product Management, Generative AI, RAG Models, Large Language Models (LLMs), Cross-Functional Leadership, Customer Interviewing, Business Case Development, Roadmap Strategy, Risk Management

Lead Data Scientist at Resilinc, Oct 2021 - Jan 2023 · 1 yr 4 mos, Greater London, England, United Kingdom, As a pioneering member of the data science team, I played a key role in shaping the company’s data science initiatives, reporting directly to the CPO and leading a small team. I developed and deployed innovative machine learning solutions to improve risk assessment, and commodity price management •Raw Material/Commodity Price Prediction (Patent Pending): Developed a state-of-the-art machine learning model to accurately predict raw material prices 3 to 6 months in advance, enabling manufacturing companies to make proactive purchasing decisions and reduce procurement costs. Conducted extensive market research to identify key drivers of commodity price fluctuations, providing actionable insights to mitigate supply chain risks. Designed an automated strategy for commodity managers to optimize asset allocation, integrating failure mitigation modules to minimize financial exposure. Built commodity price hedging models with 72% accuracy, empowering businesses to implement more effective risk management strategies and safeguard profits. •Disruption Vulnerability Index: Directed the development of a machine learning-based risk assessment tool to evaluate supply chain vulnerabilities, significantly improving strategic decision-making and operational resilience. Led and mentored a small team of data scientists, driving technical innovation and ensuring project alignment with business goals to deliver high-impact solutions. Key Skills: Leadership, Machine Learning, Supply Chain Risk Assessment, Commodity Price Prediction, Predictive Modeling, Python, Market Research, Data-Driven Strategy

AI Engineer Manager (COE) at Prudential plc, Aug 2018 - Jun 2020 · 1 yr 11 mos, Singapore, Led the design and deployment of machine learning solutions to automate and optimize key business processes in the fintech sector. Delivered high-impact models that significantly improved operational efficiency and profitability. •Claims Adjudication Automation: Spearheaded the automation of claims processing using anomaly detection and ensemble models, increasing processing efficiency from 13% to 65%. •Dynamic Pricing Models: Led the development of constraint-based pricing models for medical insurance products, achieving a 15% reduction in pricing. •Customer Retention Models: Directed the creation of churn prediction models, driving a 36% decrease in policy lapse rates across diverse markets. •Managed stakeholder engagement with C-suite executives, delivering strategic updates to the Global Head of AI. •Mentored junior data scientists, fostering technical expertise and aligning project execution with business goals. •Oversaw end-to-end deployment with CI/CD pipelines using Jenkins, Artifactory, and Openshift, ensuring scalable and secure solutions. Key Skills: Leadership, Stakeholder Management, Deep Learning, Ensemble Models, Anomaly Detection, Churn Prediction, Dynamic Pricing, Python, Keras, CI/CD (Jenkins, Artifactory), Cloud Deployment (Openshift)

Data Scientist at Prudential plc, Sep 2016 - Jul 2018 · 1 yr 11 mos, Mumbai, Maharashtra, India, •Regulatory Compliance Automation: Developed ML models to automate the analysis of 0.7 million hours of call data with 90% accuracy, leading to £26 million in cost savings by streamlining compliance processes. •Customer Propensity Models: Designed data-driven customer propensity models that increased product upgrade campaign responses by 60%, significantly improving marketing effectiveness Key Skills: Machine Learning, Customer Analytics, Predictive Modeling, Python, LSTM

Analyst at Edelweiss Tokio Life Insurance, Mar 2015 - Sep 2016 · 1 yr 7 mos, Mumbai Metropolitan Region, Developed predictive models to support financial risk management and improve forecasting accuracy. •Asset-Liability Monitoring: Built regression models to monitor asset-liability ratios, achieving a 5% mean absolute error (MAE) for enhanced financial stability analysis. •Premium Loss Forecasting: Designed spline regression models to forecast premium losses with a 10% MAE, enabling more accurate financial predictions and risk mitigation. Key Skills: Regression Analysis, Financial Forecasting, Risk Management, Predictive Modeling, Data Analysis, Python, Statistical Modeling

Education

Master's degree, Mathematics and Statistics, University of York

Bachelor of Engineering (B.E.), Computer Science, Anna University Chennai