Sanket Palchaudhary

Designed and implemented data-driven automation and bottleneck-detection frameworks for construction industry clients, applying optimization thinking to improve operational throughput and reduce process inefficiencies.
Built structured analytical and exploratory data pipelines in Python and Excel to track project KPIs, applying statistical analysis and feature engineering to identify bottlenecks and recommend workflow improvements to engineering and management teams.
Led cross-functional team coordination across engineering and client stakeholders, translating technical findings into clear narratives for non-technical leadership and managing deliverables and timelines — directly analogous to working inside a product studio with PMs and engineers.

Developed production-ready Python scripts using OOP principles for data ingestion, cleaning, and exploratory analysis across 20+ unstructured data sources — demonstrating ability to write clean, maintainable code beyond ad-hoc notebooks.
Built pivot table dashboards and reporting systems to visualize operational KPIs, saving 10+ hours/week of manual reporting and communicating insights to non-technical leadership.
Applied ML model-preparation workflows including feature engineering, pandas pipelines, and statistical profiling for pattern and anomaly identification on real-world datasets.

Implemented a pick-and-place pipeline on an industrial robot using ROS Melodic and Python, applying real-time decision-making algorithms in a live manufacturing environment.
Gained direct exposure to sensor data processing and model-driven automation in large-scale industrial settings — closely aligned with manufacturing client optimization work.