Diana Hsieh is the Head of Product and Co-Founder at Correlated. She thrives on working with enterprise software startups. She was previously the first PM at infrastructure startups, including Cockroach Labs and Timescale. Before that, she was a VC at Norwest, focused on investing in early-stage enterprise software companies. Diana is always on the hunt for her next favorite coffee shop on weekends.
Datacast Episode 119: Experimentation Culture, Immutable Data Warehouse, The Data Collaboration Problem, and The Rise of Data Contracts with Chad Sanderson
Chad Sanderson was the Product Lead for Convoy's Data Platform team, which includes the data warehouse, streaming, BI & visualization, experimentation, machine learning, and data discovery.
Previously he worked on Microsoft's AI Platform team and led Data initiatives at SEPHORA and Subway. He has built everything from feature stores, experimentation platforms, metrics layers, streaming platforms, analytics tools, data discovery systems, and workflow development platforms.
His love of the data space has also allowed him to implement open-source and SaaS products (early and late-stage) and build cutting-edge technology from the ground up.
Datacast Episode 113: Data Applications, Real-Time Analytics, and Cloud Product Management with Shruti Bhat
Shruti Bhat leads product management and marketing at Rockset. Before Rockset, she led Product Management for Oracle Cloud, focusing on AI, IoT, and Blockchain. Previously, she was the VP of Marketing at Ravello Systems, where she drove the start-up's rapid growth from pre-launch to hundreds of customers and a successful acquisition. Before that, she was responsible for launching VMware's vSAN and led engineering teams at HP and IBM. Shruti has a bachelor's in computer science engineering and an MBA from UCLA Anderson.
Datacast Episode 108: Computer Vision, Product Management, and Enterprise Investing with Tom Rikert
Tom Rikert is the co-founder and CEO of Masterful AI, the training platform for computer vision that helps developers build models faster and with much less labeling. He is a former VC and invested in enterprise software and AI/ML at Andreessen Horowitz. Before VC, he held product management roles at Wildfire (acquired by Google), YouTube, and Autodesk. He began his AI/ML journey at MIT and started his career as an engineer at Silicon Graphics. Tom lives in the Bay Area with his wife and daughter and loves going fast, whether on a mountain bike or flying racing drones.
Datacast Episode 98: Building Developer Tools, Managing Platform Products, Fostering Diversity, and Enabling Real-Time Data Applications with DeVaris Brown
DeVaris Brown is the CEO and co-founder of Meroxa, a VC-backed company enabling teams of any size and level of expertise to build real-time data pipelines in minutes, not months.
Prior to founding Meroxa, DeVaris was a product leader at Twitter, Heroku, VSCO, and Zendesk. When he’s not sitting in front of a computer, you can find DeVaris behind a camera capturing moments in time, at the stove whipping up the finest delicacies, or behind a set of turntables, moving a sea of people through music.
Datacast Episode 92: Analytics Engineering, Locally Optimistic, and Marketing-Mix Modeling with Michael Kaminsky
Michael Kaminsky is the co-founder of Recast, a marketing optimization platform, and the co-founder of Analytics Engineers Club, a training course for data analysts looking to improve their engineering skills. He is passionate about helping organizations “make better decisions faster.” He has experience applying econometric research methods to environmental economics, child welfare policy, and medical treatment efficacy. He studies Spanish, reads, and pets dogs around Mexico City in his spare time.
Datacast Episode 87: Product Experimentation, ML Platforms, and Metrics Store with Nick Handel
Nick Handel is Transform's CEO and Co-Founder. Before Transform, Nick was Head of Data at Branch International in the micro-lending space.
Before Branch, Nick held a variety of roles at Airbnb, both as a Data Scientist & Product Manager. He was on the Growth team that founded the Experiences product and the Data Platform team. His work includes launching Airbnb's ML platform, Zipline, building the company's data science team, helping with the company's initial international expansion, and leading the data science team that launched Airbnb's Trips product.
Before joining Airbnb, Nick was a research economist at BlackRock. He is an avid trail runner, climber, skier, and adventurer, much of the time with his dog Huckleberry.
Datacast Episode 85: Ad Exchange, Stream Processing, and Data Discovery with Shinji Kim
Shinji Kim is the Founder & CEO of Select Star, an intelligent data discovery platform that helps you understand your data. Previously, she was the CEO of Concord Systems, an NYC-based data infrastructure startup acquired by Akamai Technologies in 2016. She led the development of Akamai’s Internet-of-Things data platform for real-time messaging, log processing, and edge computing.
Prior to Concord, Shinji was the first Product Manager hired at Yieldmo, where she led the Ad Format Lab, A/B testing, and yield optimization. Before Yieldmo, she analyzed data and built enterprise applications at Deloitte Consulting, Facebook, Sun Microsystems, and Barclays Capital.
Shinji studied Software Engineering at the University of Waterloo and General Management at Stanford GSB. She also advises early-stage startups on product strategy, customer development, and company building.
Datacast Episode 83: Startup Scrappiness, Venture Matchmaking, and Thinking In Bets with Leigh-Marie Braswell
Leigh-Marie Braswell is an investor at Founders Fund.
Before joining Founders Fund, she was an early engineer & the first product manager at Scale AI, where she originally built & later led product development for the LiDAR/3D annotation products, used by many autonomous vehicles, robots, and AR/VR companies as a core step in their machine learning lifecycles. She also has done software development at Blend, machine learning at Google, and quantitative trading at Jane Street.
She is originally from Alabama, graduated from MIT, and loves to play poker, run long distances, and scuba dive.
Datacast Episode 81: Research, Engineering, and Product in Machine Learning with Aarti Bagul
Aarti Bagul is a machine learning engineer at Snorkel AI. Before Snorkel, she worked closely with Andrew Ng in various capacities: (1) at AI Fund helping build ML companies from scratch internally and investing in ML companies, (2) as an ML engineer at his startup Landing AI, (3) as head TA for his deep learning class CS230, and (4) as an assistant in his research lab at Stanford.
Aarti graduated with a master’s in Computer Science from Stanford, where she participated in the Threshold Venture and Greylock X fellowships. Before Stanford, she got her bachelor’s in Computer Science and Computer Engineering from NYU with the highest honors. During her time at NYU, she worked in David Sontag’s lab on machine learning applications to clinical medicine and at Microsoft Research as a research intern for John Langford (where she contributed to Vowpal Wabbit, an open-source project).