Satyansh Singh

I’m a final-year B.Tech student with a strong foundation in data analytics and Machine Learning/Deep Learning, using Python and SQL to translate messy data into actionable insights. I enjoy building end-to-end workflows—from ETL to KPI analysis and dashboarding—so stakeholders can make faster, data-backed decisions.

During my internship at Nuclear Power Corporation of India Limited (NPCIL), Narora, I analyzed real-time instrumentation data from SCADA systems, performing data validation and trend analysis to identify anomalies and reduce manual log review time. I also supported IT Web Facility data documentation workflows with data quality checks and process optimization across cross-functional teams.

In my projects, I engineered an ETL pipeline for vendor performance analysis (multi-source data into SQLite) and optimized SQL joins/CTEs to reduce redundant computation, then used Pandas to compute core financial KPIs like gross profit, profit margin, stock turnover, and sales-to-purchase ratio. I also built a supply chain delivery model using Random Forest and SMOTE to classify late-delivery risk, alongside KPI-driven analysis (including order processing time and delay distribution) to pinpoint bottlenecks by region, shipping mode, and time factors.