5 Advanced Tips to make your Data Science resume great!

Resume is important. You might have the skills but if you don’t invest in creating a great resume then you might never get the call to showcase your skills and so you might never get the job! — so investing some time in optimizing your resume can have exponential payoffs!

With that, here are 5 advanced tips to make your Data Science resume great! Note that we are assuming that you took care of basic things like typos, formatting, length (1-page please!), avoiding lies & confidential information and picking the right file format (like pdf) and we want you to build upon that now:

data science cv resume

#1: Use the “Accomplished [X] as measured by [Y] by doing [Z]” formula

Laszlo Bock (former SVP Talent at Google) suggests that everyone should highlight accomplishments instead of just stating your job responsibility & duties.

Example: Instead of saying “Improved customer engagement metrics and looked at data”; you should say something like

Reduced customer churn by 2% and adding $1M in incremental revenue per year by building a predictive model to predict customer churn and working with account executives to help them take action on that.

BOOM! That is powerful. Of course feel free to adjust the above statement based on your work.

#2: Highlight your competence trigger and Social proof 

Will Stanton suggests that you should add competence trigger and social proof in your resume. This will help you come off as competent and credible. Few things you can add to your resume:

  • A Github page
  • A Kaggle profile
  • A StackExchange or Quora profile
  • A technical blog

#3: Personalize your resume for the job that you are applying

Hat tip: Will Stanton

This is something that we built upon what Will says. You might want to personalize your resume for each role that you are applying.

For instance. If you are applying a Role where they use R, then you should make sure that R is highlighted on your resume. (Of course don’t lie. If you don’t know that then mention something else that aligns with what they use)

Also, As Will mentions, you can check the skills of existing team members on LinkedIn to figure out tools/skills that have and you should make sure to highlight these skills if you have it.

#4: Highlight Team-work and cross-functional leadership

This is something that we have noticed while conducting mock interviews on our platform especially among junior/new-grads. Data science is a team sport — So you should highlight your team-work. And also mention how you can work with cross-functional groups of software engineers, product managers, C-Level executives, etc. This is great way to stand out and show that you are truly a team-player!

#5: Make sure that you have a well-rounded resume!

Give it a final pass and make sure it is well-rounded. Ben Dias has a great list that you can use:

  • Educational background
  • Independent research experience
  • Programming skills
  • Impact!
  • Coaching, Mentoring & Management experience
  • Technical breadth and depth
  • Tools & Processes
  • An open mindset
  • Softer skills

Conclusion:

We hope this article helps you optimize your data science resume and land more interviews! If you want to prepare for your interviews then mock interviews are one the most effective ways to do so and you should consider signing up for mockinterview.co 


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