CenturyLink, the $18 billion telecom provider, is preparing to hire dozens of additional data scientists. Chief Science Officer Manav Misra -- from his seat in the CenturyLink Cognilytics business -- is leading the charge. But what exactly are his key priorities for all of that big data talent? Misra shared his insights with Information Management this week.
First, a look at the bigger picture: Misra co-founded Cognilytics -- which CenturyLink acquired in December 2014. The deal empowered CenturyLink with a range of big data and analytics capabilities -- including Hadoop and SAP Hana expertise. The goal, among others, has been to blend those big data capabilities with CenturyLink's growing cloud expertise.
Fast forward to the present -- roughly four months after CenturyLink purchased Cognilytics -- and Misra says he is personally focused on three core priorities:
1. Leading the company's data science team.
2. Driving analytics solution development.
3. Meeting with senior executives internally -- while also sitting down with customers externally to discuss market trends, use cases and other big data market milestones.
Here's a closer look at each focus area.
1. Meet the Data Science Team
Misra's team is geographically distributed across the U.S. (featuring about 60 to 70 professionals) plus a similarly sized team in India. The team members have advanced degrees in statistics, mathematics and physics -- with plenty of expertise in computer science, machine learning and artificial intelligence. Team leaders typically have 15 to 25 years experience in specific verticals -- such as banking, he adds.
To solve the big data challenge a team has to have three skills, Misra says. They are:
- First, a real knack for working with the business owners to connect various insights together and solve business problems.
- Second, you need to leverage new technologies -- often, the old offerings aren't sufficient.
- Third, you need skills in statistical and machine learning.
The real trick involves connecting the dots between each talent pool. "Our statisticians will never be Hadoop experts. And our Hadoop experts will never write the types of algorithms that our statisticians develop. But those skills and others have to be fully in place across your team."
The data science team continues to expand in "leaps and bounds" -- with plans to hire roughly 30 more experts as they graduate from colleges and universities over the next few months, he says.
2. Building and Enhancing Big Data Solutions
Big data applications, of course, require underlying platforms that scale based on user need. "Within many businesses, they're surprised to learn how expensive it is for a big data team to get access to an on-premises Hadoop cluster," asserts Misra.
With that reality mind, CenturyLink's own big data efforts live in the cloud. "It's a single-button deploy," Misra says. "Choose the nodes you need, and you get a Hadoop cluster up and running."
3. Big Data Discussions
As he tours the world -- meeting with CenturyLink's team and customers -- Misra hears some familiar themes over and over again.
In particular, chief risk officers are striving to leverage big data to address cybersecurity needs. Government organizations, financial services firms and retail organizations are working overtime to protect public-facing websites and internal systems from for-profit hackers and state-sponsored hacks by foreign governments. Those efforts involve lots of data collection combined with machine learning.
At the same time, financial companies are striving to leverage big data and analytics to mitigate risk while also complying with industry regulations.
Conversations about the Internet of Things (IoT), sensor networks and wearable computing have also heated up. Within transportation companies, data from sensors will fuel predictive analytics -- helping organizations to replace mechanical parts before they fail, he notes. Within homes and large buildings, learning systems will continue to get more and more intelligent -- automatically adjusting and optimizing environmental controls to cut costs.
The wearable conversation, he says, falls into a broader conversation about IoT. Smartwatches and more will deliver rich data sets to healthcare providers -- "now, you can mine that data to the benefit of specific individuals," he says, while pointing out that companies will need to have "strong constraints" in place to ensure proper data privacy and security.
Those efforts and others require plenty of big data talent. If everything plays out as planned, additional data scientists -- in many cases, recent university graduates -- should start arriving around May.