Headline

Aspiring ML & Data Engineer | Python · SQL · Machine Learning | 3 Internships across Vi, Reliance Retail, Rallis India | IEEE Published | NMIMS ’26

About

Data Engineer and ML Engineer with hands-on experience building production-grade data pipelines and ML systems across telecom (Vodafone Idea), retail (Reliance Retail), and agri-chemicals (Rallis India/Tata Group). At Vodafone Idea, I designed and built iRoam Assist — an automated international roaming complaint diagnosis system using Apache Kafka for real-time streaming, PySpark for data processing, FastAPI for the backend API, and a 5-rule diagnostic engine. The system processes complaints from CRM, HLR, VLR, and billing systems to deliver automated root-cause analysis to customer service agents. At Reliance Retail, I built demand forecasting models using ARIMA + ML ensembles that hit 82% accuracy, directly reducing spare-parts stockouts by 25%. At Rallis India, I cleaned and engineered 200K+ records, cutting model training time by 35%. Published at IEEE ICCCNT 2024 on MST algorithm comparisons. Open to Data Engineering, ML Engineering, and AI Engineering roles — on-site in Mumbai/Navi Mumbai, hybrid, or remote. Let's connect: archit.maha@gmail.com

Location

Navi Mumbai

Work experience

AI Intern at Vodafone Idea Limited, Jan 2026 - Apr 2026 · 4 mos, Worli, Maharashtra, India, Automated complaint resolution for International Roaming using Kafka + PySpark, reducing manual triage by 60% Consolidated 5+ workflows into single UI, cutting agent handling time from 8 min to 90 sec per case

Data Science Intern at Reliance Retail, Jun 2025 - Jul 2025 · 2 mos, Ghansoli, Maharashtra, Forecasted spare-parts demand with 82% accuracy using ARIMA + ML ensembles, reducing stockouts by 25%. Built automated KPI scorecard evaluating 50+ service centers, slashing management reporting TAT by 30%

Machine Learning Intern at Rallis India Ltd, May 2024 - Jul 2024 · 3 mos, Wadala, Maharashtra, India, Cleaned, engineered, and preprocessed 200K+ records, reducing missing data by 40% and improving performance. Reduced training time by 35% through feature engineering and pipeline optimization with 78% validation accuracy

Education

Bachelor of Technology - BTech, Computer Engineering, Narsee Monjee Institute of Management Studies (NMIMS) Navi Mumbai

Don Bosco School