Headline

Lead Data Scientist | GenAI Architect | LLMs, RAG, Agentic AI Systems | Driving $M+ Business Impact through AI Innovation

About

Lead Data Scientist with 12+ years of IT experience, including 8+ years specializing in AI/ML and Generative AI, delivering enterprise-scale AI solutions with measurable business impact. My core expertise lies in designing and deploying LLM-powered systems, RAG architectures, recommendation engines, and end-to-end AI platforms that improve efficiency, automation, and revenue outcomes. I have built and scaled GenAI-driven systems across enterprise environments, including LLM-based workflow automation (Excel, PDF, Email), scalable RAG frameworks using Azure OCR and Azure GPT, and recommendation engines using LightFM that directly contributed to business ROI improvements. My work spans both predictive analytics and GenAI innovation, enabling organizations to move from experimentation to production-grade AI adoption. Beyond model development, I have led AI roadmap initiatives, stakeholder engagements, and cross-functional collaborations across marketing and product teams. I actively contribute to mentoring data science teams and driving AI adoption strategies that align with enterprise goals. I am currently targeting senior roles such as GenAI Engineer, GenAI Architect, and Lead Data Scientist, where I can continue building impactful AI systems that combine innovation, scalability, and measurable business value.

Location

Greater Bengaluru Area

AI stack

hugging face

langchain

langgraph

langsmith

mistral

openai

Work experience

Lead Data Scientist at Digi-Key Global Capability Center, Jun 2023 - Present · 3 yrs 5 mos, India, ● Built and deployed Slow-Moving Parts AI model enabling targeted promotions and delivering $1M ROI ● Developed LightFM-based recommendation engine improving cross-sell and customer engagement ● Designed end-to-end GenAI architecture for marketing automation, enabling scalable enterprise adoption ● Implemented LLM-powered automation for Excel, PDF, and email workflows (GPT & Gemini) saving 48+ hours/week ● Architected reusable RAG-based AI services framework using Azure OCR + Azure GPT ● Led AI roadmap strategy, stakeholder demos, and mentored junior data scientists ● Participated in US office AI hackathon and completed Part Association project using LangGraph & LangChain ● Recognized with Stakeholder Impact Award for measurable AI business transformation

Lead Data Scientist at Digikey Electronics, 2022 - Present · 4 yrs 10 mos, Built and deployed Slow-Moving Parts AI model for targeted promotions delivering $1M ROI. Developed Parts Recommendation Engine (LightFM) improving cross-sell and engagement. Designed end-to-end GenAI architecture for marketing automation, enabling scalable AI adoption across business teams. Implemented LLM-driven automation for Excel, PDF, and email workflows using GPT & Gemini, saving 48+ hours weekly. Architected RAG-based reusable AI services framework using AzureOCR + AzureGPT. Led AI/ML roadmap, stakeholder demos, and mentored junior data scientists. Participated in AI Hackathon (US Office) and completed Part Association Project using LangGraph & LangChain. Contributed to AI leadership initiatives within DigiKey US office, driving GenAI adoption across marketing teams.

Senior Data Scientist at Ecolab Digital Center, Jul 2021 - Jun 2023 · 2 yrs, Bangalore Urban, ● Developed Pathogen Risk Prediction System preventing $2.6M+ losses per outbreak ● Delivered $8M business protection through predictive AI modeling ● Built scalable ML pipelines using Azure Databricks and Azure Data Factory ● Implemented model drift monitoring frameworks using SHAP, ADWIN, and Wasserstein distance

Data Scientist at Trianz Holdings, 2020 - 2021 · 1 yr, Greater Hyderabad Area, Built segmentation and forecasting models contributing to $198M revenue growth. Developed time-series pricing optimization model delivering $17.5M revenue uplift.

Senior Software Engineering Analyst at Accenture, Jul 2016 - Nov 2019 · 3 yrs 5 mos, Hyderabad Area, India, Development of model for predictive analytics. Used python latest version for machine learning algorithm code. Worked closely with stake holders for the creation of proof of concept for supervised machine learning algorithm. Handled missing values in preprocessing stage for continuous, categorical features through Imputer. Outlier detection through Huber Regression or through RANSAC (Random sample consensus). Applied Grid-Search Cross-validation for Adaboost Classifier. Used different learning rate, n_estimator as parameter of CV. Find the best estimator from cross-validation and built final estimator Find the best score of cross validation and compare with the score of predicted output.

Education

MCA, Computer Science, Dr.Mgr university

Master of Computer Applications, DR mgr University