Ville Tuulos has been developing tools and infrastructure for data science and machine learning for over two decades. At Netflix, he led the machine learning infrastructure team. Currently, he is the CEO and co-founder of Outerbounds - where he’s building the modern, human-centric ML infrastructure stack, continuing the open-source product called Metaflow that he developed and managed during his Netflix days.
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 91: Collaborative Data Workspace, The Sharing Gap, and Engineering Management with Caitlin Colgrove
Caitlin Colgrove is the Co-Founder and CTO of Hex Technologies, a collaborative data workspace for building and sharing data projects using SQL and Python. Caitlin has spent her career as a software engineer building data analytics tools, first at Palantir and then later at startups including Remix and Hex. As a CTO, her focus has expanded from purely technology to growing and developing diverse and inclusive engineering teams.
Datacast Episode 90: Operational Analytics, Reverse ETL, and Finding Product-Market Fit with Kashish Gupta
Kashish Gupta is the founder and co-CEO of Hightouch, a data startup based out of San Francisco. He grew up in Atlanta, loves playing racket sports, and always wanted to be an inventor when he grew up. He studied Machine Learning in college and had a short stint at a VC firm called Bessemer Venture Partners, and ever since graduating has been working on Startups. He and his co-founders are on their 5th business idea and have finally found a product-market fit.
What I Learned From Arize:Observe 2022
Last month, I had the opportunity to speak at Arize:Observe, the first conference dedicated solely to ML observability from both a business and technical perspective. More than a mere user conference, Arize:Observe features presentations and panels from industry thought leaders and ML teams across sectors. Designed to tackle both the basics and most challenging questions and use cases, the conference has sessions about performance monitoring and troubleshooting, data quality and drift monitoring and troubleshooting, ML observability in the world of unstructured data, explainability, business impact analysis, operationalizing ethical AI, and more.
In this blog recap, I will dissect content from the summit’s most insightful technical talks, covering a wide range of topics from scaling real-time ML and best practices of effective ML teams to challenges in monitoring production ML pipelines and redesigning ML platform.
Datacast Episode 89: Observable, Robust, and Responsible AI with Alessya Visnjic
Alessya Visnjic is the CEO and co-founder of WhyLabs, the AI Observability company on a mission to build the interface between AI and human operators. Prior to WhyLabs, Alessya was a CTO-in-residence at the Allen Institute for AI (AI2), where she evaluated the commercial potential for the latest advancements in AI research.
Earlier in her career, Alessya spent nine years at Amazon, leading Machine Learning adoption and tooling efforts. She was a founding member of Amazon’s first ML research center in Berlin, Germany. Alessya is also the founder of Rsqrd AI, a global community of 1,000+ AI practitioners who are committed to making AI technology Robust & Responsible.
Datacast Episode 88: Sales Engineering and Future of Work with Evan Cummack
Evan Cummack is the CEO of Fin.com. Before joining Fin in 2021, Evan spent 10 years at Twilio, contributing to the company’s incredible growth from Series B to IPO and beyond.
Evan was born and raised in a small coastal town on New Zealand’s North Island. Despite limited access to technical expertise, he developed an obsession not only with computers and software but with the unique competitiveness and creativity of the software industry. Enamored with Noah Wyle’s depiction of Steve Jobs in the 1999 TV movie Pirates of Silicon Valley, Evan was certain the pirate life was for him.
After studying Software Engineering and Business in New Zealand, Evan headed for Silicon Valley and quickly found a home at Twilio, which would go on to become one of the fastest-growing software companies in history. Evan considers his 10-year stint at Twilio as a “Ph.D. in SaaS,” learning from “the best software CEO in the world today.”
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 86: Risk Management, Open-Source Governance, and Negative Engineering with Jeremiah Lowin
Jeremiah Lowin is the Founder & CEO of Prefect, a dataflow automation company. Before starting Prefect, Jeremiah gained extensive experience in all aspects of the modern data stack as a director of risk management, machine learning researcher, and data scientist at a number of institutional investment firms. Today, he lives with his wife and two sons in Washington, DC.
What I Learned From Convergence 2022
Last week, I attended Comet ML’s Convergence virtual event. The event features presentations from data science and machine learning experts, who shared their best practices and insights on developing and implementing enterprise ML strategies. There were talks discussing emerging tools, approaches, and workflows that can help you effectively manage an ML project from start to finish.
In this blog recap, I will dissect content from the event’s technical talks, covering a wide range of topics from testing models in production and data quality assessment to operational ML and minimum viable model.









