Collaborating Authors


Data Scientist, Machine Learning & AI - IoT BigData Jobs


Etsy is committed to advancing the fields related to E-commerce related fields by building technologies that help Etsy buyers and sellers discover and celebrate handmade goods from all over the world. We are seeking individuals passionate in areas such as Machine Learning, Data Mining, Recommender Systems, Information Retrieval, Natural Language Processing, Computational Advertising, Deep Learning and Computer Vision. Our data scientists have the opportunity to make core algorithmic advances and apply their ideas in the dynamic world of E-commerce in strengthening Etsy’s global marketplace. Data scientists can publish their innovations at top tier conferences such as KDD, NIPS, ICML, ICLR, CVPR, ICCV, WWW, WSDM, SIGIR and etc. This position would be based in Brooklyn, New York. What We’re Working On Recommendation and Personalization Natural Language Processing and Query Understanding Deep Learning Image Processing and Understanding Text Understanding Learning to Ranking for Search and Ads Fraud and Abuse Detection Large-scale Machine Learning Who You Are You share our values (below) and are looking for a company that has a solid mission. You have strong analytical and quantitative skills. You are familiar with techniques in Machine Learning, Data Mining, Recommender Systems, Information Retrieval, Natural Language Processing, Computational Advertising, Deep Learning and Computer Vision or related fields. You have a Ph.D. degree in Machine Learning, Data Mining, Recommender Systems, Information Retrieval, Natural Language Processing, Computational Advertising, Deep Learning and Computer Vision or related fields. You have strong technical and programming skills. You are familiar with relevant technologies and languages (e.g. Python, Java, C++ and etc.). You have experience in or desire to learn Hadoop/Spark related Big Data technologies. You have demonstrated the capability to review and write technical papers. You can contribute to research that can be applied to Etsy product s. You have the ability to quickly prototype ideas and solve complex problems by adapting creative approaches. You are a strong collaborator and communicator and you make the engineers around you grow and learn. What we care about Curiosity and humility. We are dedicated to learning and constantly improving. We hope you also value things like blameless postmortems and have a natural drive to figure out how everything works. Keeping it real. Etsy’s mission and values are a part of everything we do. We care about how our work affects real people in the community and enjoy opportunities to meet them. We are motivated by this mission every day. What's Next If you're interested in joining the team at Etsy, please send a cover letter along with your CV/Resume. Tell us more about your background and why you're interested in using machine learning and AI at Etsy! Feel free to point us to your latest publication and any other online presence you may have including Github, Weblogs and others.

Top Data Sources for Journalists in 2018 (350 Sources)


There are many different types of sites that provide a wealth of free, freemium and paid data that can help audience developers and journalists with their reporting and storytelling efforts, The team at State of Digital Publishing would like to acknowledge these, as derived from manual searches and recognition from our existing audience. Kaggle's a site that allows users to discover machine learning while writing and sharing cloud-based code. Relying primarily on the enthusiasm of its sizable community, the site hosts dataset competitions for cash prizes and as a result it has massive amounts of data compiled into it. Whether you're looking for historical data from the New York Stock Exchange, an overview of candy production trends in the US, or cutting edge code, this site is chockful of information. It's impossible to be on the Internet for long without running into a Wikipedia article.

Big Data Digest: Rise of the think-bots

AITopics Original Links

It turns out that a vital missing ingredient in the long-sought after goal of getting machines to think like humans--artificial intelligence--has been lots and lots of data. Last week, at the O'Reilly Strata Hadoop World Conference in New York,'s head of artificial intelligence, Beau Cronin, asserted that AI has gotten a shot in the arm from the big data movement. "Deep learning on its own, done in academia, doesn't have the [same] impact as when it is brought into Google, scaled and built into a new product," Cronin said. In the week since Cronin's talk, we saw a whole slew of companies--startups mostly--come out of stealth mode to offer new ways of analyzing big data, using machine learning, natural language recognition and other AI techniques that those researchers have been developing for decades. One such startup, Cognitive Scale, applies IBM Watson-like learning capabilities to draw insights from vast amount of what it calls "dark data," buried either in the Web--Yelp reviews, online photos, discussion forums--or on the company network, such as employee and payroll files, noted KM World.

The current state of machine intelligence 2.0


Shivon Zilis will participate in a panel discussion at Strata Hadoop World New York 2016, "Where's the puck headed?," considering the big trends in big data and explaining what the field will look like down the road. A year ago today, I published my original attempt at mapping the machine intelligence ecosystem. So much has happened since. I spent the last 12 months geeking out on every company and nibble of information I can find, chatting with hundreds of academics, entrepreneurs, and investors about machine intelligence. This year, given the explosion of activity, my focus is on highlighting areas of innovation, rather than on trying to be comprehensive.

CIB Chief Data Science Office - Vice President - London/


Data Scientist –Executive Director Role (London) J.P. Morgan's Corporate & Investment Bank New Product Development group is tasked with accelerating new solutions to market through research, strategic analysis and testing of potentially transformative concepts. A small and diverse group of engineers, data scientists and business analysts, this team works closely with the core business and external partners to identify and align innovative new technologies and business processes to the firm, creating value for our clients and disrupting current legacy processes and business models. The Role: * The Data Scientist in this role will be leading the NPD Data Science effort based out of our London office. They will recruit and develop multiple small teams, each headed by a Vice President and composed of several Associate level data scientists, that will be tasked to develop innovative analysis. They will work with the established Data Science team in New York and business analysts and software engineers within NPD, both in London and New York, to contribute to the advanced data analytics efforts of the New Product Development group as a whole.