Jakub Jurovych is a founder and CEO of Deepnote, where he and his team are developing a collaborative data science notebook. Jakub studied Computer Science at Cambridge University, focusing on Human-Computer Interaction, Machine Learning and Computer Vision. As an engineer, Jakub built tools for JavaScript development and worked on Firefox DevTools. Later on in his career, Jakub became the CTO of Operam, a company using machine learning for better marketing at companies and Hollywood studios. Jakub is also a YC alumnus and Forbes 30 Under 30.In this episode we have an awesome conversation about project management of data science. We also talk about some of the similarities and differences between data science and software engineering teams. At the end, we dive deep into the origin of his company Deepnote.

 Chelsea is a full time faculty member teaching undergraduate Data Science and Computer Science, and earned her PhD this year in Computational and Data Science. She also does casual statistical consulting at the Chatistician which aims to empower people to do their own statistics well. In her free time, Chelsea makes educational and just-for-fun statistics memes, TikToks and art. 

This week's guest is Vivek Viswanathan. Vivek is the portfolio manager of the Rayliant Quantamental China Equity ETF and is the Global Head of Research and Portfolio Management at Rayliant Global Advisors. He has a Ph.D. in Finance from UCI, a Master’s in Financial Engineering from UCLA, and a Bachelor’s in Economics from the University of Chicago. He has worked 15 years in quantitative investment management. 

Special thanks to Allie Miller for introducing me to this guest! I met Ale Koretzky soon after I moved to Hawaii and we became fast friends. I was hooked on the stories that he told me each time we met. From traveling to the US from Argentina to pursue his fascination with signal processing, to landing his band's music video on MTV Latin America, the passion the has for music and machine learning bled into every conversation that we had. I love how Ale can go from laid back and relaxed to intense and passionate instantaneously when he gets excited about an idea. Currently, Ale is the head of machine learning and audio science at Splice where he is a thought leader at the intersection of ML, signal processing, and sound a few things he knows quite a lot about. In this interview, we learn about Ale's experience learning the signal processing field, his music career, and the main reason why some ML projects fail. I hope you enjoy the episode!

Chanin Nantasenamat is a good friend of mine and an incredible teacher. He is probably best known for his educational videos about data science and coding on YouTube via the Data Professor and Coding Professor channels.Chanin’s research interest is at the interface of biology, chemistry and computer science (encompassing interdisciplinary areas such as bioinformatics, cheminformatics, chemogenomics and proteochemometrics) for exploring the underlying origins of protein function and its modulation (i.e. inhibition or activation). Such understanding holds great implication for the discovery of novel bioactive compounds with therapeutic activity. His research group also develop bioinformatics databases, softwares and web servers for addressing perplexing biological problems. In this episode we talk about how someone can break into data science we also touch on the content creation journey and the incredibly wholesome story of how the Data Professor came to be.

With advanced degrees in computers and secondary education, along with several IT certifications, Dr. Perez brings more than 35 years' experience to the podcast as an IT/higher ed. professional. Having served as Business Intelligence Specialist at NC State University and currently serving as Senior Systems Analyst/Team Lead at the NC Department of Health & Human Services (DHHS), Perez stays active in the IT community with more than 11,000 LinkedIn followers. In addition to his fulltime leadership role at DHHS, Joe was named Chief Technology Officer at SolonTek corporation in October 2020. A highly-recommended international keynote speaker, data analytics/visualization expert, and specialist in efficiency/process improvement, he is indeed a much sought-after resource. When taking a break from work, Joe sings, plays the piano, composes songs, does guest appearances on nationally-recognized podcasts, and has performed PSA's & voice-overs for schools and other organizations. He also serves as speaker, interpreter, & music director to his church’s Hispanic ministry and (if there's any time left) enjoys publishing a monthly military newsletter. "I’m a firm believer that if I’m not innovating, I’m stagnating," says Joe.In our episode we talk about how to get over the fear of public speaking and how important the story is for conveying data science insights.

Welcome to Ken's Nearest Neighbors 50th episode special! Today we are going to mix it up. One of our favorite guests, Christina Stathopolous volunteered to turn the tables and interview me today. Super excited to get to share a bit more of my own story with you. I also always love chatting with Christina! Before we start, I have another bit of great news. the KNN team has signed an exclusive sponsorship with Z by HP. This sponsorship will allow us to expand our capabilities and continue to improve the podcast listening experience. I'm so excited about this news, and I'm happy we can share it on our 50th episode!

Aash Viswanathan is a Senior Data Scientist at Atlassian with a focus on monetization. He was previously a Product Data Scientist at LinkedIn supporting new feature development on LinkedIn Learning. Aash was also a Data Analyst at scooter-rental startup Lime, where he worked on fleet analytics. He holds a degree in Economics from the University of Chicago. In this episode we learn about Aash's biggest challenges breaking into the analytics career path. He actually applied to LinkedIn 5 times before landing the job. We also touch on the psychological side of success in this field and how obsession can be either a positive or negative force. I hope you enjoy our chat!

I had the pleasure of interviewing Eugene Yan. he works at the intersection of machine learning and product to build pragmatic, customer-facing ML systems. He also writes & speaks about effective data science, data/ML systems, and career growth.Currently, He is an Applied Scientist at Amazon shipping ML and recommends systems to help customers read more.On his website, he shares what he’s learned on shipping ML systems, with a pragmatic and product slant. He’s written 119 posts and 215,291 words so far! In this episode, we learn about how Eugene broke into data science from a psychology background. We also go through the challenges of breaking into the US job market. I learned quite a bit about the visa process and how different countries can have different visa quotas. Finally, we touch on the importance of end to end data science and how sharing your work can help you to make your own luck. I had a great experience getting to know Eugene better through this interview, and I hope you learn a lot from this episode!

Today I had the pleasure of interviewing Edward Raff. Edward a Chief Scientist at Booz Allen Hamilton where he leads their Machine Learning research group. He’s also a Visiting Professor at UMBC where he works closely with the DREAM and IRAL labs, and teaches courses in the Data Science department. He received his PhD in Computer Science from University of Maryland, Baltimore County (2018) while working full time. Edward is the author of the JSAT which is a java based machine learning library, and is interested in applying machine learning to malware, fairness, and biometrics. He has also written the book “inside deep learning” where he focuses on finding the perfect balance between math and implementation of deep learning algorithms. In this episode we learn about how Edward’s career in machine learning was kicked off by a happy accident while studying abroad, how machine learning is being applied to malware detection, and how a data career contracting for the government may be different than one working for a private company. I hope you enjoy!