Jun 2024 – May 2025 · 11 mos · Bengaluru, Karnataka, India · Hybrid

• At Sigmoid, I pioneered strategic Generative AI initiatives, developing transformative enterprise solutions and significantly advancing data-driven innovation for global clients.
• I won a prestigious month-long Generative AI hackathon, competing against over 50 top developers from companies including Tiger Analytics, McKinsey, and TCS Research. My team built an end-to-end AI product recommendation solution on Azure with a React frontend, securing a $1.5M contract with a major CPG client.
• I developed "Data Companion," an advanced enterprise-grade Text2SQL solution built on AWS Bedrock, Snowflake, and Claude 3.5 Sonnet, achieving 90% query accuracy through enhanced query optimization and deep contextual understanding. The platform was showcased at AWS Tech Summit 2024 in Las Vegas and generated $1M revenue due to rapid deployment capabilities.
• I spearheaded the creation of a multi-agent Generative AI recommendation engine on Azure, integrating Retrieval-Augmented Generation (RAG), dynamic knowledge graphs, and semantic search to deliver precise product recommendations tailored to complex customer needs, built on robust enterprise-grade architecture.
• Additionally, I led an innovative proof-of-concept exploring Generative AI's potential to automate traditional machine learning workflows, streamlining forecasting model selection, feature engineering, and hyperparameter tuning via natural language interactions.
• I architected "Visualize," a next-generation platform enabling users to create analytics dashboards through natural language, powered by advanced LLMs for data interpretation and visualization. This innovation reduced dashboard creation time dramatically—from days down to minutes.
• I also innovated an industry-first Generative AI system for automated Power BI dashboard generation, employing specialized LLMs to interpret user requirements and generate sophisticated DAX queries, enabling effortless, natural language-driven report creation.

Jun 2023 – May 2024 · 11 mos · Bengaluru, Karnataka, India

• Pioneering Automated Trading Innovations: From a blank slate to a fully operational trading powerhouse, I led the development of an advanced automated trading system. This system features streamlined user login, dynamic algorithm deployment, and precise execution, revolutionizing the approach to automated trading.
• Crafting Cutting-Edge Algorithms: Engineered and refined four proprietary algorithms that enhance strategic decision-making in trading. These tools are designed to optimize performance by prioritizing essential risk and money management protocols.
• I ventured into the realm of AI with the creation of a state-of-the-art AI application for stock market analysis. This tool provides a holistic suite of analytical capabilities, from data sourcing from Yahoo Finance to the integration of technical indicators, volume analysis, and the latest financial news via Google News. It also includes statistical insights and forecasts using the ARIMA model, allowing users to conduct thorough analyses and make informed investment decisions.

Feb 2022 – Jul 2023 · 1 yr 5 mos · Bengaluru, Karnataka, India

• In my role as a Bixby Voice Enhancement Leader and AI Researcher, I spearheaded a team of data scientists and researchers to push the boundaries of Samsung's Bixby voice assistant framework.
• Beyond technical expertise, I fostered a culture of innovation by leading the AI council for Large Language Models (LLMs), exploring their potential integration with Bixby. This collaborative spirit extended to prestigious universities like MS Ramaiah Institute of Technology and Vellore Institute of Technology, where we advanced research in areas like multivariate anomaly detection and out-of-domain problems.
• My technical contributions directly impacted Bixby's functionality and user experience. I led the development of several key tools, including:
• A device feedback solution that leverages LLMs to generate comprehensive incident reports, streamlining the development process for engineers.
• Another innovation – a highly technical, end-to-end Automatic Anomaly Detection library. This Python library empowers developers and platforms to detect anomalies with just one line of code, simplifying the resolution process for various Bixby usage patterns globally.
• I also spearheaded the development of a classifier system that utilizes advanced methods to distinguish between relevant and irrelevant user requests, ultimately enhancing Bixby's user experience.
• Furthermore, I played a crucial role in projects that analyzed user feedback text and logs. By implementing summarization and classification models, alongside log analysis techniques, we were able to identify root causes of issues and ensure data privacy through the development of transformer models for handling sensitive data detection. These contributions directly translated to a more responsive and secure Bixby for users worldwide.

Oct 2017 – Feb 2022 · 4 yrs 4 mos · Bangalore

• As a Data Science leader, I fostered a collaborative and innovative environment, building a team of experts and spearheading the use of PowerBI for impactful business reporting.
• I championed technical expertise in areas like Reinforcement Learning and optimization, acting as the single point of contact for applying AI to optimize supply chain operations.
• My leadership resulted in impactful projects like the development of an AI-powered supplier selection system and a material duplicate resolution application that leveraged cutting-edge tools and technologies.
• Additionally, I implemented a solution that reduced optimization time by over 90%.
• My technical capabilities are further exemplified by my research on predicting product lifecycles and the development of various machine learning models.
• I experimented with different algorithms and libraries to deliver solutions for entity data deduplication, demand forecasting, and inventory analysis.
• I also built a machine learning model to analyze time series data and identify factors influencing inventory stock levels across plant locations

Nov 2015 – Sep 2017 · 1 yr 10 mos · Chennai Area, India

• During my tenure as a Data Scientist at Caterpillar, I utilized machine learning to improve industrial processes (e.g., reduced injector misfires), automate defect detection (e.g., PCB inspection using CNNs), and create innovative solutions.

Sep 2011 – Oct 2015 · 4 yrs 1 mo · Bangalore · On-site

• As a seasoned Technical Coordinator with a proven track record in international software sharing projects, I excel in managing the technical aspects of Engine and Exhaust subsystem development.
• My deep understanding of communication protocols like CAN, UDS, KWP, and J1939 allows me to effectively bridge the gap between engineering teams.
• Throughout my career, I've successfully coordinated projects from inception to completion for industry leaders like Kubota, HINO, and MHI in Yokohama, Japan.
• My ability to resolve software reset issues and facilitate knowledge transfer ensures project success and drives business expansion.