Datacast Episode 96: Data Science Training and The Power of Education with Merav Yuravlivker

Datacast Episode 96: Data Science Training and The Power of Education with Merav Yuravlivker

Merav Yuravlivker is the Co-founder and Chief Executive Officer of Data Society. With over ten years of experience in instructional design, training, and teaching, she started her career teaching elementary special education in NYC public schools through the Teach for America program. She went on to join the International Baccalaureate Organization, where she developed deep expertise in online training, assessments, and recruitment. She also taught as a Kaplan GRE instructor, where she ranked as one of their top 10% instructors based on student surveys.

Merav found her passion for education and knew that she wanted to make an impact on an even larger scale. She recognized the importance of data literacy and began her data journey by learning how to program and design best practices for students during her free time. Six months later, she left her full-time job to focus on building Data Society along with her co-founders. Over the past seven years, she and her team have developed customized, industry-tailored data science training solutions that educate, equip and empower an organization’s workforce to achieve its goals and expand its impact.

What I Learned From Tecton's apply() 2022 Conference

What I Learned From Tecton's apply() 2022 Conference

Back in May, I attended apply(), Tecton’s second annual virtual event for data and ML teams to discuss the practical data engineering challenges faced when building ML for the real world. There were talks on best practice development patterns, tools of choice, and emerging architectures to successfully build and manage production ML applications.

This long-form article dissects content from 14 sessions and lightning talks that I found most useful from attending apply(). These talks cover 3 major areas: industry trends, production use cases, and open-source libraries. Let’s dive in!

Datacast Episode 95: Open-Source DataOps, Building In Public, and Remote Work Culture with Douwe Maan

Datacast Episode 95: Open-Source DataOps, Building In Public, and Remote Work Culture with Douwe Maan

Douwe Maan is the founder and CEO of Meltano, an open-source DataOps platform. Before joining Meltano, he was hired as the tenth employee at GitLab, later becoming an Engineering Manager. While at GitLab, he spent six months traveling the world, visiting colleagues in 14 different countries. In 2019, he joined the internal Meltano project at GitLab and quickly became its General Manager. In early 2021, Douwe led Meltano in spinning out of GitLab to become an independent startup, raising seed funding from investors led by Alphabet's GV.

Datacast Episode 94: Modern Metadata Management, Open-Source Adoption, and Early-Stage Culture with Mars Lan

Datacast Episode 94: Modern Metadata Management, Open-Source Adoption, and Early-Stage Culture with Mars Lan

Mars Lan is the co-founder and CTO of Metaphor Data, a startup that offers a Modern Metadata Platform to solve many complex organizational data challenges, such as data discovery and data governance. He also co-created the popular open-source project DataHub while working as the Tech Lead of the metadata team at LinkedIn. Mars received his Ph.D. in Computer Science from the University of California, Los Angeles.

Datacast Episode 93: Open-Source Development, Human-Centric AI, and Modern ML Infrastructure with Ville Tuulos

Datacast Episode 93: Open-Source Development, Human-Centric AI, and Modern ML Infrastructure with Ville Tuulos

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

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

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

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

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

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.