Mani Sai Kamal Darla is an engineering professional with over 8 years of experience in analytics, data science, data modeling, and cloud technologies. He currently works as a Senior Analyst at Walmart Inc. in Bentonville, AR, where he develops data-driven solutions across e-commerce and technology domains. His professional journey spans roles in major organizations including Amazon Robotics, Global Innovation Exchange, and Bharat Electronics Limited, where he has consistently applied analytical approaches to solve complex business challenges.
Mani earned his Master of Science with a Data Science focus from the University of Washington (2021-2023, GPA: 3.75/4.0) and his Bachelor of Technology from the National Institute of Technology, Surathkal (2013-2017, GPA: 8.46/10.0). His academic coursework included data-driven modeling, machine learning, parallel programming, and big data analysis, providing a strong foundation for his current work.
In his current role at Walmart, Mani manages Certificate Lifecycle Management for over 16,000 certificates across the organization and has worked on SSH Key placement process optimization that reduced queue times and SLA by 50%. During his tenure at Amazon Robotics, he led data analysis teams and deployed Tableau dashboards that saved 13 hours per week of reporting time. He also implemented machine learning models including ARIMA and Prophet for forecasting, contributing to a 55% improvement in drive units OEE and $1 million in cost savings.
His technical skills encompass database technologies (SQL, NoSQL, MongoDB, MySQL), programming languages (Python with libraries like Scikit-learn and Pandas, JavaScript, Bash), big data platforms (Spark, Hadoop, Snowflake, Databricks), and visualization tools (Tableau, Power BI). He holds certifications in Alteryx Designer Advanced, AWS IoT, and CompTIA Security+. Mani has also worked on diverse projects including developing CNN and LSTM models for Parkinson's disease detection, automated defect detection using computer vision with over 1,200 ultrasound images, and parallelized finite element analysis using CUDA on GPU systems.