Month: July 2017

How To Hire a Modern Data Miner

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Let’s jump right in, hiring and interviewing takes on many forms with various philosophies in play, Tim Graettinger has developed a philosophy based on the needs of an outdated headhunter, reviewing an outdated HR manual.  Perhaps, if today’s headhunters would consider today’s date, this is the digital age where a mobile philosophy focused on, who can use the tools of data mining, just might establish a positive interviewing process which gets better results. The past hiring structure is interfering with today’s high tech business needs.

On the other hand, to effectively communicate expectations and build confidence, there must be a mutual dependence between HR and the candidate. It would be more productive to open an interview with a real-life business requirements question, which challenges the candidate to create a data model, provided that there is a laptop loaded with RStudio, RapidMiner, KNIME, Microsoft BI and Excel on hand. To generate synergy, the excited candidate is given a time limit to produce the result by clustering data loaded from a csv file. There is no need for a stiff, shake down, criminal investigation, masquerading as an interview to find the right person for the job. Therefore, if the candidate can produce a result within the immediate laptop, data mining environment, then, that is all the proof which is needed for HR to make a hiring decision. Today’s industries are performance based, so the data mining interview must rely on hands-on performance criteria to meet the needs of employers.

From the article, it has been found that it is inconceivable to believe that a Graduate student, fresh out of college today, without any real world, data mining, project experience, will be chosen to interview by a Fortune 500 company for a data mining position. This power packed article reinforces the urgent need for all data mining prospects to develop hands on skills, using algorithms quickly as possible, if planning to compete in the data mining arena. Enterprises need people who can use open source data mining tools to cluster data, now! The information presented in the article, has turned a future problem into an opportunity.

Greater challenges are on the horizon, now is the time to master RStudio, RapidMiner, KNIME, Microsoft BI, Excel, and gain access to the online repositories for job security. Opportunity is waiting for the person who can see the light, digging through the dark tech tunnel, while running with a backpack full of the latest data mining tools towards success. Generally speaking, the personality of the data miner is of course, a major factor. The positive attitude, backed by confidence, will prevail!