Manish Gawade
ID: CCE085870
Manish Gawade
ID: CCE085870
- Maharashtra, India
Manish Gawade
ID: CCE085870

About Manish Gawade
Detail-oriented Project Coordinator and recent graduate with a Master's degree in Data Science, bringing hands-on experience in project support, cross-functional coordination, and data operations. Proven ability to manage task allocations, track timelines, and prepare structured documentation, ensuring efficient project execution. At EMPIRE WHOLESALE MCR LTD, effectively coordinated daily operations and improved workflow management through data-driven insights. My internship at Stop The Traffik involved developing automation systems for data collection, enhancing efficiency in preparing well-structured datasets for machine learning applications. Actively pursuing roles in Project Coordination, Junior Project Management, and PMO support within technology-driven sectors, leveraging skills in stakeholder management, status reporting, and Agile methodologies to contribute to organizational success.
Employment History
Empire Wholesale MCR LTDInvite company
14th Oct 2024 to 25th Oct 2025
Operation executive
14th Oct 2024 to 25th Oct 2025
Roles & Responsibility
Managed daily store operations by coordinating staff schedules, inventory tracking, and sales reporting to ensure smooth workflow and timely restocking. Acted as key liaison between management, suppliers, and staff, facilitating communication and process improvements. Delivered exceptional customer service by resolving inquiries and issues promptly. Supported onboarding and training of new employees to uphold company standards. Implemented operational enhancements to boost efficiency and maintained compliance with quality and policy guidelines, driving consistent service excellence.
Verification Pending
Stop the traffikInvite company
1st Aug 2024 to 11th Oct 2024
Data preparation
1st Aug 2024 to 11th Oct 2024
Roles & Responsibility
Supported the Machine Learning team by collecting, cleaning, and structuring human trafficking data from news articles and public sources. Worked on an automation system to extract key information such as location, arrests, rescues, and case details from unstructured text. Achieved around 60-65% automated accuracy, followed by manual validation to ensure 100% data reliability. Reduced manual data collection time by nearly 50%, improving overall efficiency of the data preparation process. Collaborated closely with researchers and analysts to ensure high-quality, well-structured datasets for downstream machine learning models. Contributed to faster availability of clean and usable data for analysis and model training.
Verification Pending
