Businesses Can’t Wait – Learn How Automated Machine Learning Fills the Data Science Gaps

October 4th, 2018

According to LinkedIn,

“In 2015, there was a national surplus of people with data science skills. Three years later, the picture has changed markedly: data science skills shortages are present in almost every large U.S. city. Nationally, we have a shortage of 151,717 people with data science skills, with particularly acute shortages in New York City (34,032 people), the San Francisco Bay Area (31,798 people), and Los Angeles (12,251 people). As more industries rely on big data to make decisions, data science has become increasingly important across all industries, not just tech and finance. In that sense, it’s a good proxy for how today’s cutting-edge skills like AI & machine learning may spread to other industries and geographies in the future.”

Expand the Reach of Data Science to Seize More Opportunities

Demand for data scientist talent has never been greater. While project backlogs continue to grow, business opportunities are missed. In order to realize the benefits of data science, organizations need to utilize tools that will better scale and accelerate adoption.


In a 2018 case study led by Forrester Research, a well-known multinational bank recognized over $19 million of additional revenue gained from business analyst-led machine learning projects – not data scientist led projects. Using an automated machine learning platform from DataRobot, the bank’s business analysts delivered faster time-to-value by improving accuracy and productivity for pricing optimization and sales. This organization estimated at least a 10% productivity improvement for their business analysts over a period of three years. The exact revenue contributions from DataRobot projects remain confidential. The shared values are conservative.

Focus on What Matters Most

Today, there is way too much data to manually analyze. Automated machine learning solves complex problems smarter and faster than ever before. Even if you don’t want to use what-if analysis or predictive models, automation helps you efficiently find the right answers, allowing you to narrow down what to analyze and focusing your efforts on what matters most.

By leveraging the best of mind and machine, automated machine learning is the most effective way to quickly build and deploy machine learning models that power the AI-driven enterprise. Stop waiting for data scientists and begin taking machine learning and AI initiatives into your own hands - no coding required.


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