How to Get a Data Science Interview in 2019Ken JeeBlockedUnblockFollowFollowingJan 14There is almost nothing you can do that will guarantee you an interview or a job in data science.
On the other hand, there are many things that you can do that can increase your probability of getting noticed.
I have created this step by step guide to help data science hopefuls put their best foot forward and make an impact on companies and recruiters.
Over the past three years, I have scanned hundreds of job postings and interviewed with a range of companies.
I wanted to understand what my future options were while I was completing grad school.
In the process, I broke down the job application cycle into a science.
Additionally, over the past 6 months, I have spent a large portion of my time interviewing data science candidates.
Having experienced both sides of the desk in a relative short period of time, I believe that I have a unique understanding of what will really get you noticed.
These recommendations are based on the trends that I see in the industry as well as my personal experience.
Step 1: Take a Look in the MirrorIn order to position yourself well for the interview process, it is important to think about the type of role that you would like to have next.
I recommend going through job postings to determine the type of role you would like to target.
Ask yourself a couple key questions:What are my top skills?What skills do I need to improve to get the role that I want?How can I show competency in these “key” skill areas?Would I consider relocating for work?What type of company do I want to work for (size, industry, culture)?With these questions in mind, you can start thinking about how to identify opportunities and showcase your value.
Step 2: Create Quality ContentThe largest trend in the data science job market focuses on content prospective employees create.
I specifically look to see if candidates have any of the following links in their resumes:A Personal WebsiteGitKaggleTableau PublicBlogYouTubeThis is the easiest way to differentiate yourself.
If you have published content on two or more of these resources, it can really go a long way.
You should cater these resources towards the type of roles that you are targeting.
If the job listings you are most interested in all have a tableau component, I highly recommend creating a tableau public account.
If you are looking at ML engineer roles, it makes sense to have a Git account with your personal work (Github, Bitbucket, and GitLab).
While these resources are extremely valuable, they can also hurt you if they are not done well.
I recommend updating these resources before you apply.
Revise them with the same level of scrutiny that you would give to your resume or a formal email.
Working on personal projects show employers a ton about you.
It shows that you have initiative to work on projects in your own time and that you are passionate about data science in general.
Projects also show them what type of data you are interested in.
If you are applying within a certain industry, I recommend that you do some projects that are related to the field.
Step 3: Prepare Your Digital ResumeObviously, the resume is an important part of getting noticed.
At this point, there are two resumes that you should update: the traditional resume and your LinkedIn Profile.
Before updating these resumes, I like to look through 5–10 positions that I find appealing.
If they mostly require the same skill-set, I look for keywords and themes that are constant throughout.
It is important to cater your resume to these positions by highlighting experience and skills that relate to the on-the-job requirements.
If there are a couple different types of roles that you are applying for, I recommend having different versions of your resume for each type of role.
In the essence of time, I would not recommend making a resume for each individual position that you apply for.
If there are skills that these positions require that you do not currently have, I recommend doing a project to build them.
You will learn the skill-set and evidence that proves your competency.
Many people publish their resumes on LinkedIn or online.
I recommend looking through how other data scientists have formatted their resumes.
Below are links to resume templates and online services that provide useful best practices:Example 1Example 2My Traditional Resume Recommendations:Start with your technical skills.
Show relevant projects and the tools that you used.
Highlight any team work in Hackathons (definitely do hackathons).
Link to the content that you created!Aesthetics and proper editing are important, have someone else read it over for grammatical errors.
For each project, identify what you did and the impact that it provided (if applicable).
Be as specific as possible (e.
Built a Random Forrest classifier to identify if customers would make a purchase.
This led to 1320 additional conversions over the last month.
)For schoolwork or personal projects, a project section can be really helpful.
If you have less than 2–3 years of full-time experience, highlight your project experience.
My LinkedIn Profile Recommendations:Put something meaningful in your about me statement.
If you are applying to a specific type of role, make sure that this statement highlights the desired skill-set for that job.
Social proof is important.
Ask others endorse your skills or recommend youLinkedIn lets you provide more ancillary content than your resume.
Add volunteer work, fun projects, or things that interest you.
Engaging in the community or posting work related content to this platform suggests to employers that you care about your professional network.
Step 4: Be Deliberate About Your Communication ChannelHow you get yourself on a company’s radar can be the most important factor in getting you an interview.
Referral by an active employee drastically increases your chances.
A poll by Jobvite and Undercover Recruiter suggests that only about 7% of candidates apply through referrals, but ~40% of all hires come from referrals.
If you are not considering this approach, you are putting yourself at a big disadvantage.
Going through your network has other positive benefits.
You may hear about opportunities before they are posted and there are positive incentives working for you.
Many companies offer a referral bonus, and interviewers may show preference if they have a good relationship with your referrer.
Numerous resources suggest that 70–85% of job seekers actually find employment through some form of networking.
Having at least one degree of similarity with someone can go a long way.
Reach out to your school alumni network, LinkedIn network, or even your social network.
If your friend’s parent works in an industry that you are interested in, it wouldn’t hurt to get his/her thoughts.
When you are looking for a job, it never hurts to be friendly and ask questions.
Other people can benefit from you finding a job.
Most recruiters are paid based on their ability to place candidates into roles.
Reaching out to technical recruiting companies could be a great way to outsource some of your work.
They can help you identify opportunities and give you a good understanding of the current market trends.
Companies also have recruiting teams that are paid by the leads that they convert into jobs.
When applying, or before applying, I recommend reaching out to the technical recruiters at the company and establishing a relationship.
More to come about how you should go about communicating with these people.
In summary, you should make a list of the people that you want to connect with.
The list should include people in your network (school, LinkedIn, and social) or recruiters who are incentivized to promote you within an organization.
Step 5: Do Your HomeworkIt is important to understand as much as possible about a company before you approach them.
There are few things that turn me off more than a candidate who does not have a basic understanding of what the company they are interviewing with does.
I recommend researching a company thoroughly before sending a message to the point of contact that you identified in the previous step.
You should learn about the following things related to the company:The industryThe business lines and productsCompetitorsSenior leadershipThe values and mission statementHistorySize and growth trajectoryAny recent newsA few places you can find this information:GlassdoorLinkedInCompany websiteCompany press releasesAngel.
coSet up informational interviews with people in positions that you are interested in.
Again, I would reach out to these people through your network.
These are great opportunities to ask about necessary skills, things they had wished that they had learned, and how they got their job.
I do not recommend asking about a job or an opportunity with this person’s company.
If they think that you are a good candidate, they will bring up open positions and offer to recommend you.
Tips on informational interviews:Meet for coffee near themSet meetings for 30 minutes (be respectful of their time)Plan some good questions so that you have something to talk about.
I like to ask:What a day in the life is like in their role?What the culture of their company is like?What do they wish they had known when they were interviewing?How have they enjoyed working in this field?What advice would they give to someone looking to get into this field?Thank them the next day via email.
Make this customized based on the conversation that you had.
This is a good way to remember what you talked about and leave a lasting impression.
Step 6: Reach Out and Carefully Choose Your MessagingWhen you reach out to recruiters, it is important to convey a few things:Why you are interested in the role, market, and/or company.
Be sure to customize this for each company.
Current news about the company that has caught your attention.
The value that you can provide to the company.
Provide some background on your experience with the skill-set necessary to succeed in the role.
In these circumstances, the recruiters will likely ask you to apply for the position.
If you made an impression on them, they will flag your application.
After they respond, make sure to thank them.
It is meaningful to me when candidates make the extra effort to continue the conversation.
Even if the recruiters do not decide to offer you an interview, they may be inclined to pass your resume along to someone in their network.
If you do not hear back from the recruiters within a week, still apply for the position and submit your resume.
There is no harm in following up again after you have applied.
Final ThoughtsI realize that this process can seem overwhelming, and trust me, I have been there.
However, I would imagine that you have already taken similar steps for previous jobs.
Hopefully, this article gives you some ideas on how to improve your value in the eyes of companies and recruiters.
If you follow this process and continue to develop your skills, I believe that you will be able to start and sustain a successful data science career!.