You're heading out to a Meetup and wondering what you should do to make the most of the networking opportunities. Or, perhaps you have an informational interview with a Data Scientist and/or Hiring Manager and want to get the most from it to help with your job application. You're worried you're going to waste the opportunity by not focusing on the right questions or, worse, make a bad impression based on the questions you ask.
The best questions to ask fall into 3 different categories
- General Job Questions - to understand the day-to-day experience and whether it sounds like a team you'd like to be a part of
- Role of the Data Science Team - to see how the Data Science team works with the rest of the organization, what types of questions they work on etc. … this can help you tailor not only your resume (e.g., softer skills you'll want to highlight - or not), but also what you talk about on your cover letter in terms of how you could create impact
- Key Requirements for the Data Science Team - what software, skills etc do they use on a regular basis (and hence likely expect you, as a candidate, to be comfortable with)
Let's go into a bit more detail on each / suggest some specific questions to ask
1. General Job Questions
- What do you most enjoy about your job?
- What's the most frustrating part of your job?
- What did you do today?
- What are the hours like?
- How would you describe the culture of the team?
2. Role of the Data Science Team
- How does Data Science add value to the company? Are projects/the team focused on areas that improve product features, drive revenue, reduce costs or some of each? What are some good examples of recent work?
- How much of what the Data Science team does is self-directed and how much is direction (i.e., 'being told') from somewhere else in the company?
- How are 'Data" people structured? For example, do all Data people (Engineers, Analysts, Scientists etc.) sit together as a team and then interact with the organization from there; or do they sit with/work directly with respective business unit teams? [Note, the experience will be different - and the skills you should highlight very different - in these 2 different cases]
- How does the company communicate data insights to management, different departments, etc..?
3. Key Requirements for the Data Science Team
- What software, tools and techniques does the team use regularly? Are there internal software suites to get up to speed on?
- What type/size of data is the team working with?
- How much general system admin/engineering is required?
- Does the team develop new algorithms, or are they implementing algorithms?
- What is the typical background of team members?
How to take action now!
Get ahead of your next chance to interact with a Data Scientist! You're probably not going to remember all these questions in the moment (or have chance to ask all of them!), so write down the 3 that matter most to you / you think will give you greatest insight on the role and its requirements and make sure to go over them (and go over them some more!) before you head out :)