Headline

Building SupplyWhy.ai | Agentic AI for Automotive Supply Chains

About

I lead data science efforts at SupplyWhy.ai, where we're building an AI-native product that helps manufacturers improve profitability, planning, and supply-chain resilience. I began my career in AI research, which taught me to approach unfamiliar problems with curiosity and scientific rigour. I later had the opportunity to apply that foundation to real-world business challenges at leading enterprise AI startups, working across industries and geographies. Forecasting has been the central thread of my career and through this work, I have delivered measurable business value for multiple Fortune 500 companies. More broadly, my experience spans predictive modelling, pricing, causal ML and, more recently, applying advances in agentic AI to build more capable decision-support systems. Alongside hands-on technical work, I have helped build and strengthen data science practices by spearheading hiring, guiding teams, mentoring data scientists, and setting quality standards. My responsibilities have also extended to solution design, pre-sales, and customer conversations by translating ambiguous business needs into practical AI solutions that people can understand, trust, and use.

Location

Bengaluru

Work experience

Lead Data Scientist at SupplyWhy.ai, Jan 2026 - Present · 9 mos, Remote

Senior Data Scientist at Thoucentric, Jun 2024 - Jan 2026 · 1 yr 8 mos, Bengaluru, Karnataka, India, 1. AI Solution Delivery: Forecasting & Pricing - Global Pricing Simulator: Team Lead (Internal DS) for a Pricing Analytics project where we improved and scaled a price-volume simulation tool for a global tobacco manufacturer. Combined statistical forecasting, price elasticity modeling, and similarity-based cannibalization logic. The tool is used by 20+ countries to enable strategic pricing decisions for their entire Tobacco product portfolio. - Demand Forecasting SaaS: Co-led the design and development of an advanced demand forecasting engine for a 100-year old Indian FMCG. Achieved a Forecast Value Add (FVA) of 11% by engineering an ensemble of time-series and ML models that accounted for weather, promotions, seasonality, and macroeconomic factors. 2. Team Building & Leadership - Revamped our Data Science hiring process and scaled our practice by directly contributing to the hiring and mentoring of 10+ members (Interns to Senior DS) through structured campus hiring drives and lateral-hires. 3. Presales & Solution Engineering - Designed and delivered high-impact RFIs, RFPs, and POCs for analytics use cases in Supply Chain (Forecasting, Trade Promotions, NPL Cannibalization) and Manufacturing (Predictive Maintenance), directly contributing to multiple successful deal conversions.

Data Scientist at Noodle.ai, Dec 2021 - Jun 2024 · 2 yrs 7 mos, Remote, AI in Supply Chain: ------------------- Data Scientist in the Supply Chain AI (SCAI) unit. Worked with multiple Fortune-500 customers on Demand Forecasting projects. - Fortune-500 Beer Manufacturer: Delivered Forecast Value Add (FVA) of 13% - Major Lighting Corporation: Delivered FVA of 15% - Fortune-500 FMCG: Delivered FVA of 21% - Fortune-500 Food Processing Company: Improved weekend demand forecast accuracy by >20% AI in Manufacturing: -------------------- - Collaborated with a prominent steel manufacturer as a part of the Manufacturing Asset Health AI (AHAI) team to mitigate unplanned equipment downtime. Deployed time-series models, focusing on Time to Failure and Anomaly Detection, resulting in a reduction of equipment downtime across multiple assets. - Developed an innovative AutoML solution for Predictive Maintenance. This innovation enhanced the scalability and accuracy of Time-to-Failure and Anomaly Detection models, addressing various use-cases effectively.

Data Scientist (Intern) at causaLens, Dec 2020 - Jun 2021 · 7 mos, Greater London, England, United Kingdom, Interned as a Data Scientist in the Marketing team - focusing on Innovative Applications of Causal ML - Devised use-cases for applying Causal ML methodologies across various sectors, including Banking, Marketing, Insurance, Telecommunications, E-commerce & Retail, Manufacturing & IoT, Transport & Logistics, and more. - Executed proof-of-concept data science projects, including: 1) Developing Credit Risk Models for SME Lending 2) Creating Predictive Lead Scoring Models for B2B Enterprises.

Research Intern at University of Luxembourg, Feb 2020 - Mar 2020 · 2 mos, Belval Campus, Luxembourg, - A part of the Legato Team of Prof. Stephane Bordas doing research on Physics Informed Deep Learning in the area of Biomechanics. - During my time there I studied about different Neural Network architectures used to solve and discover both Ordinary and Partial Differential Equations related to physics.

Education

Bachelor of Science, Mathematics & Computer Science with specialization in Artificial Intelligence, Shiv Nadar University

City Montessori School