CHANDRA SEKHAR

• AI driven BI transformation: Led the development of an Agentic AI solution for Business Intelligence utilizing Large Language Models (LLMs), cutting ad-hoc BI requests by 50% and boosting conversion rates via autonomous data analytics. • Built a Looker-integrated AI-powered RCA agent that automates root cause analysis for product funnels by combining LLM- based reasoning, thus reducing investigation time and accelerating product decision-making. • Embedded Analytics Infrastructure: Led end-to-end design and rollout of in-app embedded BI infrastructure (Looker), improving customer retention by 10% MoM and boosting analyst productivity by 40% through automated reporting. • Churn Reduction: Reduced customer churn from 30% to 20% by leading the development and deployment of a Churn Prediction Model, enabling the Customer Success team to proactively intervene at-risk accounts. • Revenue Strategy: Uncovered $3 Million in untapped revenue by analyzing unadvertised product catalogs, leading to the creation of Product Recommendation System. • Cost & Infrastructure Optimization: Optimized Looker semantic models to reduce Databricks cloud spend by 35% and improve query performance by 50%; established a Data Governance framework for scalable, unified BI layers. • Experimentation: Conducted A/B test and hypothesis driven experimentation to improve the customer conversion funnel - leading to an uplift of 20% in User engagement. • GTM and Sales Analytics: Conceptualized the "Opportunity Analyzer" tool for high-GMV clients (>$1M), transforming sales motions and increasing sales conversion rates from 10% to 65%. • Analytics Enablement: Designed and delivered training modules for 60+ in-house analysts and services staff, standardizing analytical rigor, improving onboarding efficiency, and institutionalizing data culture across the firm. • Growth Analytics: Built an LTV-driven analytics framework optimizing CAC-to-LTV tracking and marketing ROI by identifying key growth drivers across acquisition channels

Played a pivotal role in the Product & Analytics vertical during Meesho's hyper-growth phase, focusing on user engagement, fraud prevention, customer experience, and operational efficiency. • Risk & Fraud Strategy: Built an automated fraud detection system using statistical models to identify RTO, return and identity Fraud, delivering annual savings of USD $1 Million (2% of platform revenue) • User Engagement: As a product manager, led the development of Journeys gamification feature, resulting in a 4% increase in orders per user across the platform. • A/B Testing & Retention: Architected end-to-end experimentation framework for Meesho's Growth vertical, running hypothesis-driven experiments across gamification (Journeys, Leaderboards) and Video Influencer catalog conversion campaigns, delivering a 5% uplift in orders per view. • Machine Learning & Analytics: Built multivariate regression models to identify key drivers of NPS. Partnered with GMs of Growth and Operations to drive initiatives to improve Product quality and delivery time, and CX resolution time. • Owned P&L for Catalog Upload process: Led product catalog upload optimization initiatives, streamlining processes to reduce upload time by 30% and saving USD $250K annually.

Provided engineering analytics to major clients (Chevron, Shell, ONGC), utilizing algorithms to reduce Non-Productive Time (NPT) during drilling operations • Alerts and Predictive Modelling: Developed solution to interpret reservoir conditions from Well data to provide real time alerts for Washout, stuck pipe, Sandpipe Pressure • Reduced drilling Non-Productive Time (NPT) by 20% by developing an ML-driven casing torque fingerprinting tool that enables real-time identification of downhole casing damage.

• Startup Scale: Joined as the 5th employee, contributing to growth to 50+ employees and a $600K Seed Round from IAN investors and OLA founders. • CX Leadership: Built and led a 15-member Customer Experience team from the ground up, driving NPS from 40% to 70%, a 30-point uplift improving service quality and customer loyalty. • Product Growth: Led the product development - “Sponge Bucket” (a two-wheeler wash and detailing program, increasing customer retention by 30%.

• Research based CAPEX Optimization: Optimized tubing size specifications for the Abadi field through advanced research and simulation, reducing required wells from 12 to 10 and cutting projected CAPEX by $250 M. • Process Improvement & Cost Savings: Led a Continuous Improvement initiative to improve technical data management practices, saving $36K/Portfolio/year

Advanced Product Management, Product Management for AI

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Data Analytics with Generative AI | Gen AI Leader | Machine Learning Specialization

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