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  • Top 3 Machine Learning Trends to watch out for in 2017

    Machine Learning Trends

    Machine Learning has come a long way from being a method of data analysis for analytical model building to become the strongest progression tool for understanding today’s data-driven world. In a steadily evolving tech landscape, almost every application that is being developed today must be an intelligent application if it wants to be relevant and successful to our modern needs. Chances are you’ve heard about major companies using this machine learning technology, from Tesla and Google’s self driving cars, to amazing breakthroughs in the medical field with machines capable of predicting illnesses, and countless other examples. We don’t need to look very far to see the ways machine learning affects our lives, from grocery shopping to medical check ups, it is all around us!
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  • Why It Makes Total Sense to Create a Tech Talent Pipeline

    Tech Talent Pipeline

    The Internet of Things, machine learning, big data, and cloud computing are driving a push towards niche technology, especially among-st startups. The only problem is hiring the right talent.

    Tech hiring is difficult because there are so many specialties with lots of different skill sets, but you can circumvent that by focusing on curated talent. In many ways, it is essential for any company focused on building cutting-edge products.

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  • Why “learning” to hire for Machine Learning experts is what your startup needs

    Machine Learning experts

    Companies like Google and startups like Clarifi have one thing in common: they have identified the highly evolving symbiotic relationship between their need and importance of exploiting the power of systematic machine learning approach. For example, Google’s Translate and Photos along with Voice Search is a result of applying machine learning on existing domains. Clarifi has used machine learning to develop software and understand videos, which can add value to their company as an advertisement tool. This relationship has naturally altered the hiring process for ML experts. Companies today face immense competition (especially in the Silicon Valley) to find and attract new talent in the Machine Learning and Data Sciences domains to be ahead of competition. This in turn has impacted factors that Hiring Managers need to consider while scouting for, interviewing and having on board their most-poached category of employees, the Data Scientists. Here are the big three factors that recruiters and hiring managers would have to deeply ruminate about when it comes to Machine Learning openings.
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  • If you are a Data Scientist, you’ve struck gold!

    Data Scientist

    As global economy becomes more and more dependent on data collection, analysis, trends and predictions, aspiring data scientists are living in a golden age and can look forward to bagging their dream job. Glassdoor came up with the list of “best jobs in America”. It’s another matter altogether that about half of them is related to technology. What we found extremely promising is that the position of a data scientist appears at the top of the list! Not just this, it also topped the categories “career opportunities” and “job score” ranking. As we talk about you making it to this list, we’re looking at nothing less than a median base salary of $116,840. So now that we know we’re about to strike gold, let’s look at the who, what and how of that big jackpot!
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