The 5 Roles That Every Data Science Team Must Hire Posted on : Nov 24 - 2020

Building a data science product is quite like constructing your home. Using this analogy let’s look at the five roles and skills that the best data science teams hire for.

The CEO of a large financial services firm was a big supporter of advanced analytics. He decided to get his organization started on the path towards data science.

How did the organization plan this journey? By recruiting data scientists, of course! They hired 1000 data scientists, each at an average cost of $250,000 a year. Data scientists are hard to come by, so the CEO was very proud of this achievement.

Several months and millions of dollars later, the business benefits were not there. And upon further investigation, the organization found that these ‘experts’ were not data scientists at all!

McKinsey reports that neither this firm’s CEO nor the human resources group understood the data scientist role. They naively assumed that a bunch of high-priced technical experts could transform the organization into a data-driven one on their own.

Data scientists often come with excellent machine learning skills, but they stumble at choosing the right business problems to solve. They struggle to scale the algorithms in production. And, they fail terribly in translating the data insights into a format that business users can consume.

Data science is a team sport. Every team must hire five roles if they are serious about data-driven decision making.

Building successful data science teams

Creating a data science solution is not very different from building your home. It’s intuitively that simple to understand but practically as tedious to execute. We will look at the five data science team roles by contrasting them to the five roles needed to construct your home.

1. Data Translator - the “Architect”

An architect is one of the most critical roles in construction. She discovers the aspirations of homeowners and determines the feasibility of land use. Translating user needs into building sketches, she lays the foundation that the rest of the construction team can build upon. She ensures that the home is functional, safe, sustainable, and delivers on the promise.

Like an architect, a data translator is the best hope for a business in protecting their investment in data science. The data translator understands a user’s business needs and helps identify the most relevant projects to execute. She translates the requirements into a format that the data science team can understand. Her role continues throughout the project and is crucial in creating an actionable end-product that users can adopt for decision making.

Skills needed: Data translators are domain experts who are proficient in business analysis. With a strong understanding of data, they are excellent team leaders and communicators. They are skilled in general-purpose data tools such as Microsoft Excel. View More