Artificial intelligence makes it workable for us to open our cell phones with our faces, ask our virtual assistant’s questions and get vocalized answers, and have our undesirable emails sifted to a spam folder while never addressing them.
The effect of AI and data science doesn’t stop at the capability to make the lives of people simpler, these programs have been created to decidedly affect almost every industry through the streamlining of business procedures, the improving of customer experience, and the completion of tasks that have never been conceivable.
All the tech connectivity we are creating in the world is spewing out so much data, we need a massive amount of people to translate that data into information. And this “creation of data” will never slow down in your lifetime. That creates the rise of a whole new career designed around data analytics and pools data science and artificial intelligence talents in a whole different level.
A recent Forbes post by Bernhard Schroeder reveals how the demand fordata science skills is growing exponentially as the supply of skilled applicants is growing at a slower pace. It’s a great time to be a data scientist entering the job market.
The January 2019 report from Indeed showed a 30% increase in demand for data scientists year over year and a 348% increase since 2013, a dramatic upswing. But while demand, in the form of job postings, continues to rise sharply, searches by job seekers skilled in data science grew at a slower pace (15%), suggesting a gap between supply and demand.
Similarly, data from technology job site Dice showed the number of data science job postings on its platform, as a proportion of total posted jobs, has increased about 33% year over year, and the site considers data science a “high-demand skill.” Dice noted that the job postings are from companies in a wide variety of industries, not just tech. The number of job postings for the related and much-talked-about skill of deep learning has more than doubled year over year, according to Dice.
Still from the article, in August 2018, LinkedIn reported that there’s a shortage of 151,717 people, right now, with data science skills in the U.S., based on data from its platform. Combine that with a 16% discrepancy between job postings and job searches on Indeed, it’s evident that demand for data scientists outstrips supply. Data scientists are becoming crucial in turning the massive amount of data companies capture into action. Yet, academia is still struggling to propagate data science.
Given the high demand for data scientists, that salaries for the position are also elevated. According to an annual Dice Salary Survey, the role of data scientist carries a six-figure in a year.
Now what are exactly the high-demand roles in data science and AI? We gathered the information from Analytics Insight for top AI career paths to date.
A data scientist is liable for gathering data and analyzing it. Data scientists have foundations in cutting-edge math and statistics, advanced analytics, and machine learning and AI. In an organization, data scientists extract helpful data from an ocean of information. In analyzing the information, they make inferences and accumulate insights and use them to support the business.
Data scientists typically are expected to have some fluency in at least one programming language — Python and R being the favorites. Data scientists also are expected to have experience in tools like Hive, BigQuery, AWS, Spark, and Hadoop, as well as training in statistical modeling, machine learning, and programming.
.Artificial intelligence architects are answerable for the overall needs of artificial intelligence projects. The key role is to making and keeping up architecture utilizing leading AI technology frameworks. This job has parts of data science, solutions specialist, and technology expert all wrapped into one position.
Artificial intelligence architects need to oversee the 10,000-foot view of an AI deployment project to comprehend overall mission objectives, realize the various ways to deal with applying AI to those objectives, and organize teams to achieve those objectives. They additionally need to perceive how the AI is utilized in a company that requires a profound comprehension of the different AI patterns, capabilities of AI platforms, and the state of data in the company.
Machine Learning Engineer
The job of a machine learning engineer is at the core of AI projects and is appropriate for the individuals who hail from a foundation in applied research and data science.
Machine learning engineers ought to likewise be able to apply predictive models and leverage natural language processing when working with colossal datasets. To get recruited, it will help if candidates are profoundly knowledgeable about agile development practices.
Most job postings additionally expect applicants to be specialists in artificial intelligence, deep learning, and neural networks, with solid computer programming skills, analytical skills, and experience with cloud applications.
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