Why Hire A Data Scientist When You Can Outsource With MasterCard?

Analytics — the golden nectar of the business world.  The finance industry has been on the data bandwagon for decades, always ready to leverage the newest technology.  This week MasterCard Advisors, the credit company’s services subsidiary, injected an undisclosed sum into a Chicago-based analytics provider called Mu Sigma.  A fresh way to help retail understand consumer buying patterns?  Wikibon analyst Jeff Kelly thinks so, calling this an opportunity for businesses to essentially outsource a data scientist.  He discusses the story on this morning’s NewsDesk show with Kristin Feledy (see full video below).

Kelly says that the capital will be used to jumpstart a long term partnership between the two firms. What is it they’ll be working on? He explains that MasterCard intends to tap into Mu Sigma’s expertise in order to help retail clients make sense of consumer purchasing trends.

Like every other major financial services firm, MasterCard is sitting on a treasure trove of data: it knows what customers buy, where and when they make their purchases, and what products they are tend to pick up in certain scenarios. What Mu Sigma brings to the table is a broader picture of consumer behavior.  MasterCard’s transactional data acts as the marrow-rich stock underlying Mu Sigma’s complete entree, enhancing the raw ingredients as something more palatable for clients.

Mu Sigma serves up about 2,500 data scientists around the globe, and it has years of developing specialized algorithms for large organizations. MasterCard just has to present a set of requirements, ship its data off to the Mu Sigma HQ, and stream the insights back to merchants that rely on its services to process customer transactions.  The benefit to the merchants is a more complete picture of their customers, enabling improved marketing, recommendations and loyalty.

The Wikibon analyst believes the analytics outsourcing market has a lot of potential.  Big Data is becoming a pilar of a business’ competitive advantage, and MasterCard is but one of countless service providers looking to layer analytics as a consultancy, a central cog in data-driven industries.  Kelly doesn’t expect most businesses out there to dedicate a significant portion of their annual budgets to hiring an in-house team of data scientists, creating an opportunity for MasterCard to extend the data scientist as an enhancement of their services.

The only problem is in the long term for businesses that outsource their analytics; what’s the cost of failing to develop an in-house team of data scientists?  As software get smarter and the services industries diversify, Kelly notes, the outsourced data scientist could become a costly loss should the partnership come to an end.  See Kelly’s full analysis below:

photo credit: Mykl Roventine via photopin cc
Maria Deutscher

Maria Deutscher

Maria Deutscher is a staff writer for SiliconANGLE covering all things enterprise and fresh. Her work takes her from the bowels of the corporate network up to the great free ranges of the open-source ecosystem and back on a daily basis, with the occasional pit stop in the world of end-users. She is especially passionate about cloud computing and data analytics, although she also has a soft spot for stories that diverge from the beaten track to provide a more unique perspective on the complexities of the industry.
Maria Deutscher


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