How to Hire a Data Scientist & Find Solutions in Your Data

April 3, 2017 10:59 am PDT | Open Data

If you’re like many public sector organizations or governments, you’re awash in data. A data scientist could help you make use of all that information. But what type of data scientist is right for your organization? What skills should you look for during the hiring process and what salary should you expect to pay?

During her Merav Yuravlivkerpresentation at Socrata Connect, Merav Yuravlivker, CEO of Data Society, a data science training platform, shared insights around these questions. From the hiring process through to project development and management of data scientists, leadership is essential. “It’s your job to make sure that the data scientists you hire are used to their full potential,” says Yuravlivker.

The 3 Components That Make Up Data Science

Data science is the intersection of three big domains:

  1. Programming, or knowing how to tell the computer what to do

  2. Industry knowledge, a deep understanding of the problems in the field

  3. Mathematics and statistics, or understanding how the world works in terms of numbers

Here’s the good news: According to Yuravlivker, a background in math and statistics is not required to implement a data analytics program. “What you do need is industry knowledge,” says Yuravlivker. This allows you to identify problems, and know how to solve them.

Data science skills include everything from software engineering to machine learning. You don’t need to look for all those skills in one candidate, however. Your needs in a data scientist will vary based on several factors: your organization’s mission, function, and maturity level, to name a few. If your organization is early in the maturity cycle and just beginning to collect data, for instance, you simply don’t need someone with machine learning knowledge.

“Don’t just go out and hire any data scientist,” cautions Yuravlivker. “There is a range of what a data scientist is, so be aware of what function you want a data scientist to provide you and your team.”

Digging In: Data Scientist Job Titles

There’s a continuum of expertise for the data science field. Here are three primary roles:

  • Data Analyst: If your organization is just starting to use data science, you’ll likely want to start by hiring a data analyst. You might not require the expertise of a data scientist. Data analysts wrangle and manage data, and create basic visualizations and analyses. A data analyst can craft your organization’s data-related policy. The salary range for this position, according to Payscale.com, is $40,308 – $80,986.
  • Data Modeler: One level up in expertise, data modelers have a better understanding of your data and its source, and can do some basic modeling. According to Payscale, the salary range for this position is $53,324 – $117,677.
  • Data Scientist: Data scientists ask questions, understand what data needs to be collected, and build algorithms to get information into the real world. Data scientists are not cheap, says Yuravlivker, listing their salary range as $91,000 – $150,000.

Those are just a few of the job titles in the field: There are also data architects, database administrators, front-end developers, program managers, and many more people who may be necessary for a strong, effective data team.

In hiring, think about your organization’s objectives: If you’re looking to identify problems you can address with data, you’ll want a candidate with knowledge of both your industry and mathematics. If your goal is to tell stories visually, look instead for someone with industry and programming knowledge.

Digging In: Ideal Skills, Experience, and Traits

When you’re hiring a data scientist, seek out candidates with an educational background in a math or statistics-related topics, along with complementary skills, such as programming, says Yuravlivker. Technology experience is an obvious requirement and, as well, look for real world experience analyzing data and building algorithms. If possible, have candidates share samples on Github or Dropbox, so you can see their work.

Soft skills count, too. Here are some ideal traits in a data scientist:

  • Inquisitive: Look for candidates who are interested in your organization’s mission and goals, and understand the connection between the data and the issue you’re trying to solve
  • Storyteller: Data scientists have to be able to understand the data and then explain their findings, telling a compelling story through visualizations, presentations, and data products
  • Relentless and meticulous: Candidates should have a lot of attention to detail, and be patient enough to track down and resolve bugs (no matter how long it takes)

Don’t underestimate the importance of your role — as a leader — in hiring the right candidates for your organization, setting up the team in a way that maximizes results, and creating conditions that will lead to powerful usage of data. “Without your leadership, it doesn’t matter if you have the most talented data scientists on your team, because their ideas won’t be heard or implemented,” says Yuravlivker.

Interested in Learning More?

Watch Merav Yuravlivker’s full presentation from Socrata Connect and download her presentation.

 

Discount — Work with Data Society

Do you work with data or have a team member who would like to improve their skills? 

Data Society offers courses such as “Introduction to R and Visualizations” and “Clustering and Finding Patterns.” For the remainder of April 2017, Data Society is giving a 10% discount to any member of the Socrata community who signs up for classes. If you’ve read this blog post, you’re in.

Use the discount code SOCRATA when you sign up and you’ll receive 10% off your purchase.