Deputy Manager - Analytics
1. Analyzed data from different production sources and provided data analysis to improve the current process by identifying and eliminating the pitfalls in existing systems.2. Spearheaded complex structured and unstructured data analysis initiatives using SQL and Python to define and document key performance indicators (KPIs),driving business insights resulting in a $1.4 million impact.3. Implemented defect detection in manufacturing parts using Convolutional Neural Networks (CNN) and computer vision techniques to automatically identify defects, leading to reduction in defects in manufactured parts by 14%.4. Created optimization and predictive models using Python to forecast equipment failure and optimized maintenance schedule leading to reduction in downtime by 12 % and maintenance cost by $ 1.1 million. 5. Incorporated Internet of things (IOT) in production facility for data collection and management from shop floors using SQL and provided data insights of production process using Tableau. 6. Project in-charge for production of new engine models in assembly line including end to end strategy planning, scheduling, process engineering and execution of new mass production capacity worth more than $65 million.7. Developed and implemented machine learning models, including Random Forest, to analyze process variables to diagnose faults and identify root causes in systems, leading to accurate issue diagnosis and implementation of corrective actions.8. Conducted in-depth analysis of business systems for potential process development and recommended business processes re-engineering to senior leaderships and stakeholders to drive end to end process optimization.