Himanshu Laddhad

About Himanshu Laddhad

Data Analyst and Data Scientist with 2+ years of industry experience building things that actually get used — forecasting models that changed procurement decisions, analytics pipelines that replaced manual workflows, and AI systems that turn messy B2B data into structured insights. I started in mechanical engineering and spent most of my time not on machines, but on the data they generated. That\'s a longer way of saying: I found data analytics by accident, then pursued it deliberately. What I\'ve built: → Retail demand forecasting pipeline (Walmart dataset, LGBM + Optuna, 18% MAPE improvement over seasonal baseline across 45 stores / 143 weeks) → Conversational Mapping Intelligence Agent for B2B supply chain EDI/XML integrations — LangGraph + ChromaDB RAG, 6 integration patterns automated (PartnerLinQ) → Competitive Pricing & Market Intelligence Platform — aggregates pricing, assortment, and trend data from 8+ real-world sources for SKU-level merchandising decisions → Agentic Analytics Assistant: multi-agent NL-to-SQL system with AI-selected visualizations and Redis→ Customer churn prediction + expected value targeting (LGBM + Optuna) and NLP review mining (LDA topic modeling)Industry background: 2 years at JCB India (Top 5 global construction equipment manufacturer) in supply chain analytics — S & OP dashboards, rolling demand forecasts, OTIF optimization — & quality analytics — root-cause analysis, KPI pipelines, defect reduction. I\'ve worked with SAP-integrated supply chains across 6+ export markets. This gives me operational context that most analytics candidates don\'t have. Technical stack: Python (LightGBM, XGBoost, Scikit-learn, LangGraph, Pandas, PySpark), SQL (PostgreSQL, BigQuery), Tableau, Power BI, Databricks, LLaMA APIs, FastAPI, SAP, AWS (CLF-C02), Azure AI (AI-900). Open to full-time roles in: → Retail Analytics (demand planning, pricing, merchandising, consumer insights) → Product Analytics (growth analytics, experimentation, user behavior, funnel analysis) → Data Science (ML modeling, forecasting, NLP, LLM integration) → Supply Chain Analytics (non-manufacturing: logistics, procurement, distribution) Outside work: I follow upcoming tech more seriously than is probably healthy, think about optimising chores as a hobby problem, and am genuinely fascinated by how data changes the way large organizations make decisions — not just the models, but the moment someone actually uses the output. West Lafayette, IN → Open to relocation across the US h••••••••@gmail.com | Open to opportunities from July 2026

Experience

1. Data Analytics & Ai Engineer

   Partnerlinq

   Jan 2026 — Present · US

   Architected a Conversational Mapping Intelligence Agent for B2B supply chain EDI/XML integrations using LangGraph and Groq API, automating schema-to-schema translation across 6 integration patterns and eliminating manual mapping effort • Engineered a multi-intent NLP routing system with independent confidence scoring across 4 intent types (explain, generate, modify, simulate), backed by ChromaDB RAG retrieval for schema-aware response generation • Delivered a production-ready Streamlit analytics frontend with structured output validation, a 9-sprint Jira roadmap, and a full data dictionary covering EDI/XML/XSLT/JSON schemas — translating a complex B2B integration problem into an analyst-usable tool

Education

• Sardar Vallabhbhai National Institute of Technology, Surat

  Bachelor of Technology - BTech, Mechanical Engineering

  2019 — 2023

• Purdue University Daniels School of Business

  Master of Science - MS, Business Analytics and Information Management