Renita Augustin
About Renita Augustin
Renita Augustin is a Supply Chain Data Analyst at General Mills with a background in software engineering and machine learning.
Current Role at General Mills
Renita Augustin currently serves as a Supply Chain Data Analyst at General Mills, a role she began in December 2021. In this position, she applies her expertise in data analysis to improve supply chain operations. Her responsibilities likely include analyzing supply chain data, identifying inefficiencies, and proposing data-driven solutions to enhance operational performance.
Previous Role at MAQ Software
Before her current role, Renita worked at MAQ Software as a Software Engineer from 2020 to 2021. During her tenure, she would have been involved in software development projects, contributing to coding, testing, and deploying software solutions. Her experience at MAQ Software provided her with valuable skills in software engineering and collaborative team projects.
Internship Experience at BUDSTA Analytics & Insights
In 2019, Renita completed a two-month internship as a Machine Learning Engineer at BUDSTA Analytics & Insights Pvt. Ltd. in Mulund. During this internship, she gained hands-on experience with machine learning algorithms, data preprocessing, and model training. This role helped her build a foundation in machine learning principles and their applications in analytics.
Education in Computer Engineering
Renita earned her Bachelor of Engineering degree in Computer Engineering from Fr. Conceicao Rodrigues College of Engineering, where she studied from 2016 to 2020. Her education provided her with a strong foundation in computer science, programming, and engineering principles. This academic background has been instrumental in her career as a data analyst and software engineer.
Microsoft Certified Data Analyst Associate
Renita is certified as a Microsoft Certified Data Analyst Associate. This certification underscores her proficiency in data analysis tools and techniques. With this credential, she has demonstrated her ability to analyze data, derive insights, and present data-driven recommendations, further validating her expertise in the field.