Dhanesh Padmanabhan

* Worked on building an AI platform for automating machine learning model development including feature store, modeling workbench and model risk management. Stack: React.js, Java, Ray, FastAPI

I serve as an Enterprise Architect in a Product Strategy Unit advising on Digital Public Infrastructure (DPI). This unit has been part of IIIT Delhi until Jan 2026 and Wadhwani AI from Feb 2026. * Conduct architecture and product reviews of national-scale digital platforms for usability, engineering performance and cloud cost footprint * Develop edge AI systems employing deep learning–based biometric and identity workflows

Worked on few Agentic AI applications: * Chatbot application leveraging RAG, MCP tools for database querying and ML forecasting using Langchain for macro economic data analysis and forecasting application * Invoice Extraction using Vision Language Models, OCR+LLMs and LLM as a judge in Agno * Media Monitoring using a multi-agentic approach leveraging RAG in Agno

Leading analytics, credit risk modeling and ML engineering teams for Lendingkart’s unsecured business loan portfolio. Team Size: 30-35. * Managed a team of AI/ML engineers who develop computer vision solutions, fraud identification algorithms and a feature store for realtime feature serving * Responsible for development & maintenance of underwriting ML models - bureau-based programs, cash flow-based underwriting, behavior score-based underwriting for unsecured business loans/personal loans * Supported active portfolio management and policy improvements in liaison with risk teams * Supported collections with collection prioritization using ML models * Supported renewal/top-up pre-approved programs for existing customers

Areas: Data Sciences & Engineering Leading engineering & data science teams that are responsible for developing platforms & AI models for AI-based extraction services in healthcare and financial applications such as adverse event report extraction and invoice/contract processing automation. Team Size: 25-30. * Developing a Machine Learning platform for lifecycle management of AI model development & governance, model publishing in a modern microservices architecture * Developing a Data platform that supports governance, lineage tracking, streaming & batched workflows for AI & analytics applications * Reusable AI models for Natural Language Processing and Document Extraction applications using state of the art deep learning models

Areas: Data Sciences & Engineering I led the analytics, data science and data engineering teams for Truecaller that are responsible for internal analytics and development of core algorithms like spam detection, name election & user segmentation for ads. Team Size: 11 spread across Europe and India * Responsible for the analytics infrastructure and data processing pipelines processing roughly 16 billion events per day * Development of AI and ML roadmap for the organization and mentoring data scientists in development of machine learning applications * Successfully managed the migration of the analytics infrastructure with a petabyte scale Hadoop cluster to Google Cloud Platform

Areas: Web Analytics, Big Data, Machine Learning Team: Data Science Engineering, Mar 2013 onwards * Mentoring and managing a team of data engineers who are responsible for development of data & ML products and production support. * Developed product roadmaps and strategy for batched & realtime data tools and infrastructure in liaison with product management and product engineering teams. * Developed a complex event processing-based analytical database leveraging big data and columnar database technologies that enables quick cross-channel insights generation and machine learning model development. * Developed a Prediction as a Service platform that exposes various machine learning techniques for model development and publishing. * Production support for new client onboarding for ETL pipeline/database deployments and realtime model deployments Team: Customer Solutions, Till Mar 2013 * Development of online targeting playbook for [24]7’s clients involving user intent prediction models to achieve targets on incremental revenues. * Managing and mentoring a team of analysts & consultants in delivery of machine learning solutions and insights for maximizing outcomes through online interventions.

Research Areas: Consumer Choice Models, Portfolio Optimization * Development of portfolio optimization methods for long term strategic planning using market dynamics models, green house gas regulation models, mixed-integer and nonlinear programming techniques. * Development of consumer choice models that accurately model consumer decision making process by incorporating decision heuristics using data mining concepts. * Collaboration with National University of Singapore on consumer choice models

Areas: Pricing and Marketing Analytics for B2B IT products/services. • Managed a Return on Marketing Investment project involving market response models and optimization techniques for providing decision support on marketing investment allocation for HP’s enterprise businesses. • Managed a pricing analytics team that provided competitive price tracking and analysis, price disparity analysis, several pricing reporting analyses, and developed pricing decision support tools. • Worked on Proof-of-Concept projects on price elasticity measurements for storage products and sever level attach measurements for server options.

Areas: CRM Analytics, Predictive Analytics • Development of a web application leveraging SAS/IntrNet technology for automated data mining of purchase association patterns of enterprise products & services for a leading IT company. • Optimization of promotional contacts based on logistic regression response models and clustering techniques for a leading IT company.