What It Takes To Get Into A Top Data Science Team

IBM has tripled the size of its Data Science Elite Team to nearly 100 data scientists since 2018, who are tasked to work on more than 130 projects. This dedicated team operates independently from the services group, working with software customers.

Whether you are an existing data scientist looking to advance to a more senior role, or someone looking to dive into a data science career, a look at how IBM hires data scientists gives a good idea about this trending – and rapidly evolving landscape.

Programming required

As reported on ZDNet, Seth Dobrin, the vice president of IBM's Data and AI unit and chief data officer of IBM Cloud and cognitive software noted that the common thread for all roles on the data science team is the ability to code using Python.

Dobrin described having deep expertise in Python as “the most basic requirement” and which covers all job segments. Of course, depending on individual roles, other programming languages that you might want to brush up on or pick up might include Scala and OPAL.

While this is hardly surprising, it is worth noting that Dobrin is not just looking at cursory or basic competency at Python here. Indeed, the initial screening process entails a coding challenge that candidates have to complete on their own. Assuming you make the cut, this is followed by a coding session done over video conferencing with one or more senior members of the team.

Don’t forget the soft skills

Programming skills and an aptitude for juggling numbers are hardly the only prerequisites, however. The interview process also sees potential candidates screened for usual prerequisites such as a good cultural fit for the organization, as well as various skills required for success in client-facing roles.

With extensive travel expected of team members, the requisite skills range from good communication, “presence” and behavior. Obviously, problem-solving skills are also a must, and this is evaluated by having the candidate share their thought process when confronted with a problem where the answer isn’t known.

Let’s talk about roles

The Data Science Elite Team works with software customers to accelerate machine learning and artificial intelligence implementations. To ensure a broad range of capabilities, half the team is made up of early professionals and highly experienced employees. The other half consists of mid-career and more senior employees.

What are the exact roles in the team? While exact figures were not offered, some of the roles mentioned include:

  • Machine learning expert with a background in mathematics
  • Data engineers
  • Experts in database systems
  • Engineers adept at setting up Hadoop clusters
  • Visualization engineers (Data journalists)

The good news: just 15% of IBM’s hires for this team are internal candidates. If this is representative of the typical data science department in other firms, this means that there is ample space for career advancement.

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