Vebashini Naidoo

Vebashini Naidoo has a diverse work experience in the field of data analytics. From 2018 to the present, they have been working at rain South Africa, first as the General Manager of Data Analytics and currently as the Chief Data Scientist. Prior to their time at rain South Africa, they worked at Absa Capital as a Quantitative Analytics professional from July 2017 to September 2018. Vebashini also held a role as a Quantitative Business Analyst at Rand Merchant Bank until February 2023.

Vebashini Naidoo's education history is as follows:

- From 2010 to 2013, they attended Wits Business School and obtained a Master of Business Administration (MBA) degree. The field of study for their MBA is not specified.

- In 2016, they completed their Bachelor of Banking degree in Finance and Banking from UNISA.

- Vebashini pursued a Bachelor of Science (B.Sc.) degree in Mathematics and Computer Science from UKZN. The specific duration of their enrollment at this institution is not provided.

- Additionally, they pursued a Bachelor of Science (BSc) Honours degree in Computer Science from UNISA. The timeframe for this degree is not given.

In addition to their formal education, Vebashini Naidoo has obtained various certifications. Some of these include:

- "Building a Data Science Team" from John Hopkins University through Coursera, obtained in January 2021.

- "RStudio Tidyverse Instructor" certification from RStudio PBC, obtained in December 2020.

- "Nanodegree in Deep Learning" from Udacity, obtained in September 2020.

- "Git and Version control" certification from Dataquest.io, obtained in March 2020.

- "AWS Certified Solutions Architect Associate 2019 Course (in prep for cert)" from A Cloud Guru, undertaken in August 2019.

- "AWS Certified Solutions Architect Associate Course" from Udemy, undertaken in August 2019.

- "Mastering AWS Well Architected Framework" from A Cloud Guru, undertaken in August 2019.

- "ISYE6501x: Introduction to Analytics Modeling" from edX, obtained in May 2019.

- Various certifications related to R programming and data analysis from DataCamp, obtained between 2018 and 2019. These include courses on spatial analysis, geospatial data, forecasting, machine learning, sentiment analysis, support vector machines, cluster analysis, correlation and regression, data visualization, and exploratory data analysis.

It should be noted that no specific timelines are provided for the certifications, therefore the sequencing of these certifications cannot be determined.