This week I had the pleasure of speaking with Sergio Ramos. Sergio is a self taught data analyst from Fort Worth Texas.Coming from a background of blue collar construction and warehouse work, Sergio was fired at the beginning of the COVID pandemic and taught himself all of the prerequisite skills to become a data analyst from home with the help of his mentorIn his spare time, Sergio enjoys reading non fiction and listening to podcasts as well as strength training and boxing.

 This week I am speaking with Andrada Olteanu. They are currently a Data Scientist at Endava, Kaggle Notebooks Grandmaster, Dev Expert at Weights&Biases and Data Science Global Ambassador at ZbyHP. They have a bachelors in Statistics and a masters in Data Science and Analytics. They work to combine the artsy side of data with the technical side to create fun, educative and insightful notebooks. This was a great conversation and I hope you all enjoy.

 Christopher P Willis is Acrolinx’s Chief Marketing & Pipeline Officer, responsible for all aspects of the company’s Marketing strategy and pipeline health. Christopher has over 20 years of experience growing companies in the technology sector. Before joining Acrolinx, Christopher held leadership roles in marketing, creative, technical, and business development at companies including Perfecto, Pyxis Mobile, KPMG-CT, ModelGolf, and Cambridge Technology Group. 

 Ben Rogojan is a data engineering solutions architect with expertise in data architecture and statistics. He focuses on developing end-to-end data solutions that help take data from raw format into data products and analytics. He has delivered on projects for clients across healthcare, finance, SaaS, and technology and previously worked as a data engineer at Facebook. He maintains a strong online presence creating content for data engineers and those curious in entering data engineering career paths and is known as the “Seattle Data Guy” online. 

 Dhaval Patel is a data engineer at Bloomberg (EX: NVIDIA). He has 17 years of industry experience and has worked in different big tech companies mainly as a software engineer. He runs a youtube channel called codebasics where he teaches data science, machine learning, python, data structures and algorithms, and career guidance. 

Today I had the pleasure of interviewing Scott Cole. Scott is technically a machine learning engineer in the fintech space, but stubbornly prefers a “data scientist” title. He studied bioengineering at Clemson University before moving to UC San Diego for grad school where he developed algorithms and python packages to analyze brain wave data. Scott then went through the Insight Data Science program, and for the last 2 years has been building algorithms for detecting fake accounts on a peer-to-peer payment app. Scott’s most known for eating hundreds of burritos during grad school and curating a small database of their qualities along 10 dimensions. In this epissode we learn the origin of Scott's burrito dataset, how he narrowed his career search based on his interest, and how he is trying to create a data centric board game. I hope you enjoy the episode, I know I had a blast speaking with Scott.

Today I had the pleasure of interviewing Nick Singh. Nick is a career coach, and the best-selling author of "Ace the Data Science Interview". Previously, he held a variety of Software & Data roles at Facebook, Google, and VC-backed startups. He aspires to be the Drake of Data Science....whatever that means!" Today we learn about Nicks fascinating career journey through tech, the keys to landing the data science job, and his unique experience writting his book. I hope you enjoy the episode, I know I enjoyed our chat!

Today I had the pleasure of interviewing Gilbert Eijkelenboom. As a former professional poker player, you can find Gilbert wherever psychology and data meet. After studying behavioral science, Gilbert has built an amazing consulting career in the data and analytics space. Combining both worlds, Gilbert founded the company MindSpeaking: The human side of data. His training programs help data scientists understand the business, get buy-in from stakeholders, and tell stories with data. Last year gilbert published his best selling book, People skills for analytical thinkers that we will be giving 3 away of today. Just comment below with your favorite part of the episode with a chance to win! Today we take a deep dive into our minds. We learn about how gilbert found a passion for his work through his career in poker and consulting, how introspection and reading helped him to change how he interacted with the world, and what batman, the joker, and elephants have to do with how we communicate. I had a great time speaking with Gilbert, and I hope you enjoy the interview!

This episode of Ken's Nearest Neighbors is powered by z by hp. Hp's high compute workstation grade line of products and solutions. Ben Taylor has over 18 years of machine-learning experience. After studying chemical engineering Taylor worked for Intel/Micron in applied semiconductor building process control and fault models. After that, he worked as a quant at a hedge fund on a 600 GPU cluster. Taylor then joined a young Sequoia-backed HR startup called HireVue to run their data group. In 2017 Taylor co-founded  Zeff.ai with David Gonzalez to pursue deep learning for image, audio, video, and text for the enterprise. Zeff was acquired by DataRobot in 2020 where Taylor now works as their Chief AI Evangelist.In this episode we learn why Ben Lived in a tent in the woods during college, how introspection has changed his career and his relationships with people, and why AI is far more philosophical than you think.

 Jack Raifer Baruch is a Behavioral Scientist turned Data Scientist. A believer in lifelong learning, entrepreneur and passionate about using Data Science to improve socio-emotional development for individuals and organizations. Currently he heads the Data team at Ada Intelligence. In this episode we talk about the intersection of human behavior and data, why Jack loves online learning and certificates, and the wild possibilities for data science if we remove profit from the equation.