About Me
Jiyanshu Jain is a final-year B.Tech Computer Science (AI & ML) student at SVVV Indore, currently interning as an AI/ML Engineer at Ernst & Young. He built a production XGBoost + SHAP pipeline evaluating 3,000+ EV charging sites across 9 Indian states on Azure Databricks, and created NEURO CAMPUS — a full-stack campus platform with 8 integrated sub-apps including an NLP CV generator, ML career guidance engine, and KNN face recognition attendance system. His stack spans Python, FastAPI, GeoPandas, Scikit-learn, Azure, and Gemini API. Certified in Azure AI-900 and Oracle OCI Data Science Professional. Actively building in the agentic AI space and open to AI/ML and data science roles across India.
Skills & Technologies
Work Experience
AI/ML engineer Intern
Developed a Python (OOP) application pipeline using XGBoost and Scikit-learn to evaluate 3,000+ EV station sites across 9 Indian states; applied SHAP for audit-ready model interpretability, cutting manual analysis AHT by 50%. • Built and deployed application components on Azure Databricks; integrated REST APIs (OSMnx, Overpass) for spatial data enrichment; authored technical specifications and process documentation for end-to-end pipeline workflows. • Collaborated with cross-functional client teams to deliver insightful outputs meeting commercial milestones; optimized data processing using Pandas, NumPy, and Parquet/Feather formats across large-scale datasets
Software Engineer Intern
Developed a Python (OOP) NLP resume-parsing backend with Scikit-learn-based skill recommendation achieving 92% extraction accuracy; consumed REST APIs (Google Search Engine API, OpenStreetMap) for enriched data fetching. • Engineered automated email notification workflows achieving 95% delivery rate; transformed and processed structured data using Pandas and JSON, translating complex business requirements into practical, scalable application modules.
Projects
NEUROCAMPUS— Student Campus Cloud Network
Architected a multi-role full-stack platform (Admin, Teacher, Student, Guest) with 8 integrated sub-applications including an AI aptitude quiz engine, CV generator, and AutoSlideX; built Flask/FastAPI REST APIs with Supabase PostgreSQL and Google Gemini API (GenAI / LLM) for automated document generation, reducing faculty workload by 60%. • Delivered an NLP-powered CV generator (90% ATS pass rate), an ML-based career guidance engine (Scikit-learn, 6 CS domains), and a KNN face recognition attendance system; deployed Smart Career Guidance module on Vercel with adaptive difficulty logic and real-time performance analytics.
Education
B-tech
computer Science