Nikola Radnovic
About Nikola Radnovic
Nikola Radnovic is a Senior Software Engineer at Credit Karma, where he has worked since 2015. He has a background in software engineering and research, having held positions at YouTube, The University of Tokyo, and as a co-founder of Xendit.
Work at Credit Karma
Nikola Radnovic has served as a Senior Software Engineer at Credit Karma since 2015. In this role, he has been instrumental in leading the cloud infrastructure setup for the company's new datacenter in the UK, ensuring compliance with GDPR regulations. He is also part of the Cloud team, responsible for migrating the company's infrastructure to the Cloud using technologies such as BigQuery, Bigtable, and Google Cloud Storage. Additionally, he implemented a Jenkins setup for the Data Science and Machine Learning teams, facilitating the use of Terraform for building Spark clusters in the Cloud.
Previous Experience
Before joining Credit Karma, Nikola Radnovic co-founded Xendit, where he served as the first investor from 2013 to 2015. He also worked as a Software Engineer at ClearSlide for nine months in 2014. His early career included a Software Engineering Internship at YouTube in 2013 and a Research Internship at The University of Tokyo in 2012. Additionally, he worked as a Research Assistant in the Nuclear Engineering Lab at UC Berkeley from 2011 to 2014.
Education and Expertise
Nikola Radnovic earned a Bachelor of Science (BS) degree in Electrical Engineering and Computer Science from the University of California, Berkeley, completing his studies from 2010 to 2014. He also attended the Mathematical High School in Belgrade from 2006 to 2010, where he developed a strong foundation in mathematics and science.
Technical Skills
Nikola Radnovic possesses expertise in cloud infrastructure and software engineering. His work at Credit Karma involved utilizing technologies such as BigQuery, Bigtable, and Google Cloud Storage. He has experience with Terraform for infrastructure management and Jenkins for continuous integration and deployment, particularly for data science and machine learning applications.