Vijitha Alva
About Vijitha Alva
Vijitha Alva is a Data Scientist with over five years of experience in the data warehouse domain. She has worked at notable companies including AirAsia, APRIL, and Infosys, and holds a Master's degree in Data Analytics from Harrisburg University of Science and Technology.
Work at AirAsia
Vijitha Alva has been employed at AirAsia as a Data Scientist since 2020. In this role, she focuses on developing solutions-oriented approaches to data science projects. Her work involves applying her expertise in predictive modeling and utilizing various programming languages and tools to enhance data-driven decision-making within the organization.
Previous Experience in Data Science
Prior to her current position at AirAsia, Vijitha Alva worked as a Data Scientist at APRIL from 2018 to 2020. In this capacity, she contributed to data science initiatives and leveraged her skills in predictive modeling. She also gained experience as a Data Analyst Intern at Return Logic from 2016 to 2017, where she developed foundational skills in data analysis.
Education and Expertise
Vijitha Alva holds a Master's degree in Data Analytics from Harrisburg University of Science and Technology, which she completed from 2015 to 2017. She also earned a Bachelor's degree in Computer Science Engineering from Canara Engineering College, studying from 2007 to 2011. Her educational background provides her with a strong foundation in data science and analytics.
Technical Skills and Specializations
Vijitha Alva specializes in predictive modeling and has extensive experience in the data warehouse domain, accumulating over five years in this field. She is proficient in programming languages and tools such as Python, PL/SQL, and UNIX, which she utilizes to develop data-driven solutions and enhance analytical processes.
Career Background in Data Engineering
Before her roles in data science, Vijitha Alva worked as a Data Engineer at Infosys from 2011 to 2014. This position allowed her to gain valuable experience in data management and engineering, further enhancing her skill set in the data domain.