
Business Analyst with less than a year in ERP Transformation & IoT Analytics
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Results-driven Data & Business Analyst with hands-on experience in ERP transformation, IoT analytics, and machine learning pipelines. Proficient in SQL query optimization, EDA, statistical modeling, and Python-driven automation. Delivered measurable impact across logistics, supply chain, and FinTech domains. Seeking entry-level roles in Data Analytics, Data Science, or AI Engineering.
Unknown
B.Tech · Computer Science (Data Science)
August 1, 2022 – June 30, 2026
Klaimify Pvt Ltd
Business Analyst Intern
February 1, 2026 – Present
India
Lorry Management System - IoT & FinTech Analytics Platform
June 19, 2026 – Present
Engineered a real-time IoT data pipeline by integrating Blackbox APIs, processing 100+ daily logistics transactions with sub-second query latency via optimized database indexing. Architected a proprietary Fuel Theft Detection algorithm using heuristic analysis of sensor vs. GPS data, identifying anomalies with ~90% detection accuracy and reducing fraud-related losses by an estimated 20%. Optimized SQL query workflows to handle high-throughput vehicle tracking logs, cutting report generation time by 35% across logistics operations.
ERP Transformation - Rice Mill Supply Chain Digitization
June 19, 2026 – Present
Orchestrated end-to-end migration of 60+ users from Excel/Tally to ERPNext, achieving 100% data parity and eliminating manual entry errors across 5+ departments. Automated validation scripts and workflow triggers, reducing manual processing overhead by 40-60% and improving data integrity for executive KPI dashboards by 30%. Designed supply chain module (Gate Entry → PO → Production → SO), decreasing inventory leakage by 12% and cutting procurement lead times by 15%.
Predictive Placement Analytics ML Classification Model
June 19, 2026 – Present
Built an end-to-end ML pipeline using Python (Scikit-Learn) to classify student placement outcomes, achieving an 88% F1-score through feature engineering and hyperparameter tuning. Executed deep-dive EDA on 50,000+ data points across 10+ variables using Pandas/Seaborn, identifying key academic predictors and reducing data cleaning time by 25% via reusable preprocessing scripts.
Cultural Fit Analysis
The candidate's project diversity, spanning IoT analytics, FinTech, supply chain, and predictive analytics, indicates adaptability and a broad interest in applying analytical skills across different domains. Their current internship as a Business Analyst Intern aligns well with the target role, suggesting a clear career path and motivation. The use of various tools and frameworks (ERPNext, Git/GitHub, Jira) shows an openness to different technologies and methodologies. The academic background in Computer Science (Data Science) further supports a data-driven mindset, which is crucial for a modern Business Analyst role. The candidate appears to be a good fit for a data-centric, problem-solving culture.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving abilities and a results-driven approach, evidenced by their project outcomes (e.g., 90% detection accuracy, 20% fraud reduction, 35% report time reduction). Their experience in orchestrating ERP migration and automating workflows suggests good organizational skills and an understanding of operational efficiency. The focus on data parity and eliminating manual errors indicates attention to detail and a commitment to data integrity. While direct collaboration or leadership experience is not explicitly detailed, the project descriptions imply an ability to work within a team to deliver complex solutions.