Data science teams are a relatively new addition to most companies. The explosive growth in data science roles over the last decade has led to many different recruiting, hiring, and management practices from organization to organization.
Onboarding a new data scientist can be challenging for a variety of reasons:
As part of your onboarding process, you should make sure they have what they need to succeed in all of the different aspects of their role.
Now that you have new hires and are getting settled in, it's time to get the new employee more acquainted with your company's data science setup. This information will help them understand how you get your work done and help them find the best way to contribute to their efforts.
When you're introducing your new Data Scientist to the team, make sure that you introduce them to the engineering and infrastructure teams. This is important because it will help them build a relationship with the people responsible for creating the tools they'll be using, as well as how data is stored in their environment. If there are any other data scientists on these teams (like myself), it could be helpful for your new hire to meet me so that I can help get them up-to-speed on how things work at my company.
After introductions have been made and meetings with key players have been scheduled, use this time together as an opportunity for a tour of your office space and some Q&A about what it's like working here! Showing off our culture is also great because getting excited about our values can make someone feel like they belong here right away—something even more important when it comes time for onboarding than usual because of how stressful it can be!
Once onboarding data scientists are familiar with their team members, the next logical step is to introduce them to the rest of the company. This can be accomplished by including an introduction during general all-hands and department-specific standups. These introductions should be short and to the point. They should include a brief description of each person’s role, responsibilities, and background (i.e., what they did before joining your team). For example: “This is Elon Smith; he’s a senior data scientist in our financial services group who specializes in building statistical models for asset pricing applications. He has worked at Goldman Sachs since 2008 where he spent most of his time researching new ways to model volatility measures within fixed income markets."
Your new data scientist employee will be eager to get started with their new position, but it's an important step for them to learn about the existing analysis. You can use internal notebooks to showcase this information and what type of work you expect them to perform in the future.
These notebooks should include any existing analysis that your team has done in the past, as well as best practices in data science at your company. If there are specific projects that you would like this employee to focus on, it may be beneficial for them to see what other employees have already done so they can have some ideas before they begin their own analyses. This also shows how data science is used within your organization; it allows newer employees or those who aren’t familiar with the industry yet to see how valuable it is for companies of all shapes and sizes!
That’s it! That’s all there is to it. The first few days can be tough for a new hire, but if you take steps to make their onboarding experience as smooth as possible, you’ll have a happy, productive employee on your hands. Hopefully, by now this has been helpful for anyone wondering about how to integrate data science into the hiring process or what to do once they have hired someone. It's important to remember that every company and every industry is different so don't feel like you need to stick strictly with what we've outlined here - adapt these tips according to your own individual workplace needs... and best of luck!