Gaurav Khatavkar
About Gaurav Khatavkar
Gaurav Khatavkar is a Senior Analyst with extensive experience in data analysis and business intelligence. He holds a Master's Degree in Business Analytics and has worked in various roles across multiple companies, demonstrating expertise in statistical techniques and programming languages.
Work at Brillio
Gaurav Khatavkar has been employed at Brillio as a Senior Analyst since 2021. His role involves leveraging his expertise in data analysis and statistical techniques to support various projects. He works in Pune, Maharashtra, India, and contributes to the company's data-driven decision-making processes.
Previous Experience
Prior to joining Brillio, Gaurav held several positions that enhanced his analytical skills. He worked as a Data Analyst at Itemize from 2017 to 2019, where he focused on purchase document data extraction. Before that, he served as a Product Operations Associate at Itemize for one year. His earlier experience includes internships at MMI Inc and Brückner Machinery, where he gained foundational skills in business intelligence and data analysis.
Education and Expertise
Gaurav Khatavkar holds a Master’s Degree in Business Analytics from the University of Texas at Dallas, completed in 2017. He also earned a Bachelor's Degree in Information Technology from the University of Pune in 2014. His educational background is complemented by certifications in Google Analytics and IBM DB2 Academic Associate. He has expertise in statistical techniques, mathematical modeling, and machine learning algorithms.
Technical Skills
Gaurav is proficient in multiple programming languages, including SQL, SAS, R, Python, and JavaScript. He demonstrates strong capabilities in manipulating and analyzing large datasets, both structured and unstructured. His technical skills extend to various analysis and reporting tools such as Alteryx, SAP BI, and Kibana, as well as databases like Microsoft Access, SQL Server, and Oracle.
Statistical Techniques and Analysis
Gaurav has a solid understanding of various statistical techniques, including Logistic Regression Models, Tobit/Probit Models, and Clustering. He possesses a practical understanding of time-series analysis and econometrics, which enhances his ability to conduct predictive and prescriptive analytics. His expertise allows him to provide valuable insights through data analysis.