The investment, led by Whitehart Ventures, extends the $4.5 million Series A financing round led by Greycroft Partners, bringing DataScience's total amount of funding to more than $28 million.

The new funding round will be used to grow DataScience's team of leading data scientists and engineers who combine intellect, proprietary in-house tools, and data to drive significant business results.

'The current practices for extracting and communicating insights from data are broken,' said Ian Swanson, co-founder and CEO of DataScience. 'Existing business intelligence and analytical software tools are focused on visualizing every single way you can slice data, which fails to give users a direct and precise course of action.'

'Many of these tools output a barrage of key performance indicators, which are scattered in different emails, PDF reports, and dashboard visualizations. This results in wasted time and effort in trying to figure out where to focus to make impactful decisions,' Swanson added. 'We designed DataScience to show customers precisely what they need to know to answer their toughest questions and to collaborate on those insights so they can quickly be put into action.'

How DataScience Works:
The process begins when customers send data securely to DataScience either in real-time or as flat files. Actionable insights are extracted from the data through the use of proprietary technologies, a network of custom models, and an in-house team of data scientists. DataScience looks at predictive factors such as lifetime value, churn, and likelihood of sale, in addition to particular needs expressed by the customer (e.g. How can I improve discounting efficiency?). All of the resulting insights are published on the DataScience web application, which provides users with a host of interactive tools including categorization, advanced search, and other collaborative functions for individuals and business teams.

One of DataScience's text mining models was tooled to evaluate online reviews for common words or phrases found in the lowest reviews of a particular product. The model noticed that 'shipping' and 'poor description' were found commonly among very negative reviews -- and shared the insight with the customer via DataScience's web application. The customer's product and marketing teams then focused on improving the shipping process and bolstering the product descriptions on their online pages, resulting in a 20% decrease in negative customer reviews and a 15% increase in net promoter score.

Growing a Data Science Company & Culture:
'The demand for data science capabilities is booming across industries, and we've designed a product that leverages an ideal mix of human intellect and machine-powered analysis to serve that need,' Swanson said. 'Whether our customers have in-house data scientists or not, we're able to onboard in a matter of days, and quickly scale to deliver value across all of their business units, from marketing to customer support. Within months of service, many of our customers are seeing multi-million dollar revenue opportunities, and/or double digit improvements in their key metrics.'

In just six short months since announcing the company publicly, DataScience has signed on innovative corporations across a range of industries; from social applications like Tinder, to consumer electronics companies like Belkin.

DataScience isn't just attracting top customers, but top talent as well. Whereas many companies are having trouble hiring data scientists, DataScience is pulling talent from a pool of over 1,000 applicants a month. 'It's a true testament to the culture we've built here, and our dedication to the growth of our employees and to the data science field,' Swanson said. DataScience was recently ranked the No. 1 Small Employer among the Top 100 Best Places to Work in Los Angeles in 2015 by the *Los Angeles Business Journal. *

About DataScience:
Based in Culver City, Calif., DataScience, Inc. combines human intellect with machine-powered analysis to extract information from data that drives real business results. Founded by a team of accomplished entrepreneurs with backgrounds in data science and big data, and experience in such Fortune 500 mainstays as American Express, AOL and Sprint, DataScience traces its lineage to Sometrics, which was acquired by American Express in 2011. DataScience is backed by Whitehart Ventures, Greycroft Partners, Pelion Venture Partners, Crosscut Ventures and TenOneTen.