Neha Chaturvedi
About Neha Chaturvedi
Neha Chaturvedi is a Data Scientist at General Mills in Mumbai, India, with a background in teaching and a strong foundation in statistics and data analysis tools.
Current Position at General Mills
Neha Chaturvedi is currently employed as a Data Scientist at General Mills, a global food company, in Mumbai, Maharashtra, India. Her role involves leveraging data science techniques and tools to analyze data, extract insights, and support decision-making processes within the company.
Previous Experience as Assistant Professor
Neha Chaturvedi has experience in academia, having served as an Assistant Professor at SIES College of Arts, Science & Commerce SION(W) in Mumbai Area, India, from 2018 to 2021. During her tenure of three years, she was involved in teaching and mentoring students in the field of statistics.
Educational Background in Statistics
Neha Chaturvedi holds both a Bachelor's and a Master's degree in Statistics from the University of Mumbai. She completed her BSc in Statistics from 2013 to 2016 and subsequently pursued her MSc in Statistics from 2016 to 2018. Her formal education has equipped her with a strong foundation in statistical analysis and methodologies.
Expertise in Data Analysis Tools
Neha Chaturvedi is proficient in a variety of data analysis tools and software. She is skilled in Python, R, SPSS, and Minitab. These tools are essential for conducting robust data analysis, building statistical models, and performing data visualization.
Proficiency in Microsoft Office Tools
Neha Chaturvedi possesses strong proficiency in utilizing Microsoft Office tools, including MS Excel, MS Word, and MS PowerPoint. These skills enable her to efficiently organize, analyze, and present data, as well as document and communicate findings effectively.
Python for Data-Science Course Completion
Neha Chaturvedi has completed an NPTEL course titled 'Python for Data-Science,' earning a commendable score of 82%. The course has enhanced her programming skills in Python, specifically tailored for data science applications.