Saksham Dwivedi

I am a mathematics and mechanical engineering student who applies quantitative methods to solve real-world problems, combining rigorous statistical training with hands-on engineering insight. My work bridges data science, applied statistics, and domain-focused analytics to deliver actionable results.

During an internship at Grasim (Aditya Birla), I analyzed ferrography and spectrometric oil diagnostics to detect wear patterns and contamination trends, translating complex lubrication diagnostics into predictive maintenance insights that improved asset reliability.

My projects include forest phenology analysis using R and phenopix to extract NDVI-based seasonal metrics, ergodic systems analysis revealing non-random tournament performance patterns, and building DCF valuation models for the Indian battery industry. I automate workflows, streamline preprocessing, and emphasize reproducible code.

I bring proven analytical rigor, a knack for communicating technical findings, and a commitment to continuous learning—seeking roles where I can apply statistical modeling, time-series analysis, and financial or industrial analytics to create measurable impact.