Target is looking for a Principal Data Scientist – Business Intelligence in Minneapolis, MN. According to the post, “The Principal Data Scientist anticipates future business needs and identifies opportunities for complex analysis. Gathers and analyzes data to solve and address highly complex business problems and evaluate scenarios to make predictions on future outcomes and support decision making. Designs and drives the creation of new standards and best practices in the use of statistical data modeling, big data and optimization tools for Target.com and Mobile.” Read more
Posts Tagged ‘Target’
Last week the world learned that the hacks at Target hit more customers than originally thought – somewhere in the 100 million vicinity – and that Neiman Marcus also saw customer credit card information spirited away by data thieves. They’re not the first big-name outfits to suffer a security setback, could they be the last?
No one can ever say never, of course. But it’s possible that new tools that leverage machine learning predictive analytics could put a serious dent in the black hats’ handiwork, while also improving IT’s hand at application performance management.
A big problem in both the APM and security space today is that there’s just a ton of data coming at IT pros dealing with those issues, much of it just describing the normal state of affairs, and no one’s got time to spend reviewing that. What IT staffers want to know about are problems, which leads to a lot of rules-writing to identify thresholds that could point to issues, and to a lot of rewriting of those rules to account for the fact that things change fast in today’s world of system complexity – and to a lot of misses because of the impossibility of keeping up. Sixty percent of problems are still reported by users, not the tools IT is using, says Kevin Conklin, marketing vp at Prelert, whose machine learning predictive analytics technology is used in CA’s Application Behavior Analytics and available as Anomaly Detective for the Splunk IT apps ecosystem.
With Thanksgiving Day, Black Friday and Small Business Saturday behind us, and Cyber-Monday right in front of us, it is clear the holiday season is in full force. Apparently, retailers – both online and real-world – are doing pretty well as a group when it comes to sales racked up.
Reports have it that e-commerce topped the $1 billion mark for Black Friday in the U.S. for the first time this year, with Amazon, Walmart, Best Buy, Target and Apple taking honors as the most visited online stores, according to ComScore. Consumers spent $11.2 billion at stores across the U.S. on Black Friday, said ShopperTrak, down from last year but probably impacted by more people heading out to more stores for deals that began on Thursday night. The National Retail Federation put total spending over the four-day weekend at a record $59.1 billion, up 13 percent from $52.4 billion last year.
Not surprisingly, semantic technology wants in on the shopping action. Social intelligence vendor NetBase, for instance, just launched a new online tool that analyzes the web for mentions of the 10 top retailers to show the mood of shoppers flocking to those sources. The Mood Meter, which media outlets and others can embed in their sites, ranks the 10 brands based on sentiment unearthed with the help of its natural language processing technology. Read more