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MLOps | Is the Enterprise Repeating the Same DIY Mistakes?

In this contributed article, Aaron Friedman, VP of Operations at Wallaroo.ai, discusses why hiring data scientists isn’t the answer to unlocking ML value (especially at a time when finding qualified candidates is harder than ever).

How to Find the Mythical “Perfect Data Scientist”

There are currently over 400K job openings in the U.S. for data scientists on LinkedIn. And, every single one of these companies wants to hire that magical unicorn of a data scientist that can do it all. What rare skill set should they be looking for? Conor Jensen, RVP of AI Strategy at AI and data analytics provider Dataiku, has boiled it all down to 6 important points. 

Galileo Launches to Give Data Scientists the Superpowers They Need for Unstructured Data Machine Learning

Galileo emerged from stealth with the first machine learning (ML) data intelligence platform for unstructured data that gives data scientists the ability to inspect, discover and fix critical ML data errors 10x faster across the entire ML lifecycle – from pre-training to post-training to post-production. The platform is currently in private beta with the Fortune 500 and startups across multiple industries.

Video Highlights: Supercharging our Data Scientists’ Productivity at Netflix

In this talk sponsored by Tecton, Jan Forjanczyk, Senior Data Scientist, Netflix and Ravi Kiran Chirravuri, Software Engineer, Netflix, working in Content Demand Modeling, present one of the challenges that they faced earlier this year. This is used as a backdrop to present the human-centric design principles that govern the design of Metaflow and its internals.

Domino Data Lab Debuts New Solutions with NVIDIA to Enhance the Productivity of Data Scientists

Domino Data Lab, provider of a leading Enterprise MLOps platform trusted by over 20% of the Fortune 100, announced a series of new integrated solutions and product enhancements with NVIDIA, some of which are available now and others will be made available in the coming months. These new enhancements allow data scientists and data engineers the ability to deploy the industry’s most powerful and innovative solution to enhance productivity and positively impact business outcomes.

Panel Discussion: Needed Data Skills for 2021

In this panel discussion article, Grant Shirk, Head of Marketing at Sisu, to help both hiring managers and job seekers looking to fill these key roles, sat down with a number of senior analytics leaders to get their perspectives on hiring, recruiting, and critical skills. You’ll find their conversation below, full of insights and actionable recommendations.

Video Highlights: How to Set Up a Remote Data Science Team

The talk below was part of a joint webinar with Appsilon and RStudio on July 28, 2020. In the presentation, Appsilon Senior Data Scientist Olga Mierzwa-Sulima explains best practices for data science teams – whether they are working in the office together or fully remote.

NVIDIA’s New Data Science Workstation – a Review and Benchmark

This new whitepaper from NVIDIA’s Authorized Channel Partner, PNY Technologies, tests and reviews the recently released Data Science Workstation, a PC that puts together all the Data Science hardware and software into one nice package. The workstation is a total powerhouse machine, packed with all the computing power—and software—that’s great for plowing through data.

Infographic: How to Become a Data Scientist in 2020?

Data Scientist continues its reign as one of the most coveted jobs in 2020. In fact, as the business world becomes increasingly data-driven, there is a serious concern that the data science skill gap will continue widening and the supply of data scientist career talent won’t be able to catch up to the industries’ demand. For the 3rd consecutive year, our friends at 365 Data Science asked the data and collected their findings in a detailed annual report summarized in the included infographic.

International Women’s Engineering Day

Today is International Women’s Engineering Day 2019, and with women making up just 16% of engineering professionals, it’s important to highlight amazing women in the field, and encourage more young women to consider a career in engineering, specifically data science and data engineering in the process.