Sakshi Goyal
About Sakshi Goyal
Sakshi Goyal is a Data Analyst currently working as a Virtual Intern at KPMG Australia since 2020. She holds a Master's degree in Applied Mathematics from Panjab University and has extensive experience in data analysis and predictive algorithms across various organizations in Australia and India.
Work at KPMG Australia
Sakshi Goyal has been working as a Data Analyst (Virtual Intern) at KPMG Australia since 2020. This role is based in Adelaide, South Australia. During her time at KPMG, she has engaged in various data analysis projects, contributing to the firm's data-driven decision-making processes. Her internship has provided her with practical experience in the field of data analytics, enhancing her skills in data interpretation and analysis.
Education and Expertise
Sakshi Goyal holds a Master's degree in Applied Mathematics from Panjab University, which she completed from 2014 to 2016. She further pursued a Master's degree in Data Science at the University of South Australia from 2018 to 2019. Her academic background equips her with a strong foundation in mathematical and analytical skills. She possesses expertise in complex parametric and non-parametric methods, including Large Margin Nearest Neighbor (LMNN), and is experienced in unsupervised learning techniques such as clustering and association rule mining.
Background
Sakshi Goyal began her career as a Research Assistant at S.C.D. Govt College in Ludhiana, India, where she worked for one year from 2014 to 2015. She then transitioned to various roles in Australia, including positions as a Data Analyst at Lendlease and Peregrine Corporation, and as a Data Scientist at Spiral Data Group and the University of South Australia. Her diverse experience across different organizations has contributed to her development as a skilled data professional.
Achievements
Throughout her career, Sakshi Goyal has worked on significant projects, including the development of predictive algorithms for water pipeline failure prediction in Australian water utilities and shark sighting prediction in community services. These projects demonstrate her capability in applying data science techniques to real-world problems, showcasing her analytical skills and technical knowledge in the field.