To conclude our series on data science and analytics job searching, we wanted to cover a key, but often overlooked, step in the process: how to follow-up after your interview! If you missed them, you can also check out our previous articles on how to write data scientist resumes and tips for phone and in-person interviews.
Once you’ve gone through a few rounds of interviews, especially if things went well, you might be tempted to think that the next step is to wait, but remember it’s not over until it’s over! You want to focus on leaving a positive impression on a potential employer throughout the process, and that includes how and when you follow-up with them.
Tips for Post-Interview Follow-Up
The Art of the Thank-You Email
First things first! After in-person or on-site interviews it is expected that the interviewee (you!) will follow-up with thank-you notes. Here are our tips for what to write, who to send to, and when to send.
1. Collect business cards from your interviewers!
Throughout the interview process, make sure you’re collecting business cards from any interviewers that you speak with so that you can send them a thank-you note afterwards.
2. Write separate, personalized emails to every interviewer
Do not write the same thing to everyone! Short, 4-5 sentence emails are fine, but you should be writing unique emails to each person that interviewed you. You will really stand out if the emails are personalized based on the conversations that you had with each person. If you spoke to several people at once on an interview panel, each of them should still get a different email.
3. Reiterate your interest, provide data science/analytics project examples if relevant
A great starting point for what to write in these emails is to emphasize your interest in the particular role based on your conversation (i.e. “I’m excited that your data science team is implementing Python, and to put my expertise to use!”).
If relevant, you could also provide a link to a project, your GitHub profile, or another sample of your work that supports your note (i.e. “I know we talked about my side data projects, so I thought you might like to see the results of my March Madness bracket analysis from last year”). Make sure not to bombard your interviewers with too many links or irrelevant information – one specific project example should be enough!
4. Send the emails within 1-2 days of your interviews
In terms of timing and when to send these emails, the sooner you can send out personalized, well thought-out notes, the better! We always advise sending emails instead of traditional paper (snail) mail, because the last thing you want is for the hiring team to have made a decision before your note even arrives.
Managing Post-Interview Expectations
After the interview process is done and your thank-you notes are sent, you may need to be patient and wait to hear back. Here are some tips regarding other aspects of the post-interview process.
1. Look to your potential employer’s timeline for follow-up guidance
With so many teams hiring data scientists and analytics professionals, most employers are aware that the market is competitive, and will try to give you a sense for when they will have a decision or feedback for you after the interview.
After your thank-you emails are sent, wait to send any additional follow-up notes until after the timeline the employer has given you. If you’re working with a recruiter, they should be a good resource for letting you know when to expect a response!
2. If the status of another interview or job offer changes, let your contact know
Dealing with multiple job offers can be a tricky situation, but transparency is the best policy! If your status changes with another company you’ve interviewed with, make sure to let your contact know so that they can take that into consideration. Check out this post for more advice on how data scientists can manage interviewing with multiple companies at once.
3. Do your research on salary expectations
Before the job offer and negotiation process, make sure to do ample research on realistic salary expectations for your field. Burtch Works has published salary reports for predictive analytics professionals and data scientists, but also keep in mind what salary range the company is targeting for the role and how salaries can vary depending on location and industry. This post goes into more detail on how to evaluate job offers for data science and analytics positions.
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Want to learn more about data science and analytics career planning? Watch the webinar recording below to hear our recruiters’ best advice on interview preparation, tools and skills to learn, salaries, and more!