Aashutosh Jadhav
About Aashutosh Jadhav
Aashutosh Jadhav is a Scrum Master currently working at Thomson Reuters in Mumbai, India. He has a background in Information Technology and has held roles at Casepoint LLC and HERE Technologies, where he developed skills in Agile methodologies and project coordination.
Work at Thomson Reuters
Currently, Aashutosh Jadhav serves as a Scrum Master at Thomson Reuters, a position he has held since 2022. He works in a hybrid environment based in Mumbai, Maharashtra, India. In this role, he facilitates the understanding of Scrum principles and trains users on the Agile manifesto. He collaborates closely with leads and Product Owners to enhance delivery processes and improve team performance.
Previous Experience at Casepoint LLC
Aashutosh Jadhav worked as an Associate Scrum Master at Casepoint LLC from 2021 to 2022. His role was remote and based in Surat, Gujarat, India. During his tenure, he contributed to the implementation of Scrum methodologies and supported team dynamics in various projects.
Experience at HERE Technologies
Before joining Casepoint LLC, Aashutosh Jadhav was a Spatila Data Specialist (Project Coordinator) at HERE Technologies from 2019 to 2021. This position was on-site in Navi Mumbai, Maharashtra, India. He coordinated projects and utilized his skills in Geographic Information Systems (GIS) analysis, focusing on maintaining the quality of end products.
Education and Expertise
Aashutosh Jadhav earned a Bachelor of Science (BS) in Information Technology from the University of Mumbai, completing his studies from 2015 to 2018. His educational background provides a solid foundation for his technical skills, which include proficiency in HTML, Microsoft PowerPoint, and Adobe Experience Manager.
Skills and Methodologies
Aashutosh Jadhav possesses a range of skills that enhance his effectiveness as a Scrum Master. He is proficient in using Trello for work management, along with Jira Dashboard and Confluence for tracking team progress. His experience includes refining story estimations and streamlining backlog refinement processes, contributing to more effective planning and delivery in various projects.