So, is data science really the “sexiest field of the 21st century” as HBR put it back in 2012? Absolutely! By sexy, we mean intriguing, attractive, in high demand and offering very high pay even for entry-level candidates.
But before you get all giddy, here’s a quick reminder: data science is a competitive field. While there’s a lot of employers hiring for such positions, most are after the top talent. This means that apart from having an up-to-date skillset, you’ll also need to appear likable and position yourself as a nice cultural fit to the organization.
A strong resume, paired with an even more persuasive cover letter, should do the trick for you. So where do you begin? Check out several tips from our career team below, followed by a sample data science resume for additional context.
Go The Extra Mile to Perfect Your Skill Set
People who become data scientists have a variety of backgrounds. Some hail from the STEM field. Others have worked in software development or other business roles. While you certainly can study data science as an undergraduate or graduate student, you have other options as well.
Because this is such a popular field, there is a wide variety of online courses for those who want to develop or hone their data science skills. Take advantage of online learning platforms like EdX, Coursera, and Udemy.
And then practice what you’ve learned by doing several Kaggle projects for your portfolio.
Take Your Online Presence Beyond LinkedIn
It takes more than a LinkedIn profile to get the attention of the folks hiring for the best data science positions. You’ll need to establish a bit of an online presence that highlights your skills. Consider the following:
- Creating a professional portfolio website
- Sharing your projects and code on Github
- Creating a Kaggle Profile
Share Code With Context
The code you share on Github or Kaggle can certainly be an asset when it comes to impressing decision-makers. However, you shouldn’t simply throw every bit of code you’ve written out there.
Instead, be selective. Share only your cleanest code that has been associated with standout projects. Make sure you’ve included plenty of comments documenting your code as well, along with a quick blurb explaining just what you were trying to accomplish and what results you’ve achieved.
Here’s something else to consider: don’t let your code stand alone. Consider pairing it with a blog post or write up. This will allow you to give people a bit of context, and explain your methodologies. Again, this increases your visibility online.
Build Your Network
In many fields, the first thing you do is search job boards to find a new job. In data science, generic job boards may be the last place you’ll want to tackle.
A far better option is to start networking, both digitally and in-person. Building an online personal brand is part of the deal. Now, take the next step and engage in the aforementioned online communities to build rapport with other contributors, as well as businesses. Of course, you should also reach out to recruiters.
To further build your network consider attending meetups, events, and conferences. Also, look for open source projects that are looking for contributors. This is a great way to show your skills while also making important connections.
Resume Sample for Data Scientist (Word Version)
Download resume example (.docx)
Data Science Resume Example (Text Version)
website: [your website here]
Experienced data scientist and machine learning specialist who has spent 5+ years creating, maintaining, and perfecting predictive analytics systems for a variety of industries. Improved the efficiency of the data cleansing process, created proprietary data lakes from scratch, contributed to the development of company-wide data governance framework. Developed a predictive algorithm for the finance industry with a 99.98% accuracy rate. Interested in employing my skills as a data science manager at a large organization.
St. Louis, MO
April 2015 – Present
Currently, working as a data science consultant as part of a project designed to use both privately and publicly available datasets to gain new insights into consumer behaviors in e-commerce. Using techniques including web scraping, data analysis, machine learning, and statistical analysis. Improved customer understanding and retention by 20% by creating a predictive product recommendation engine.
St. Louis, MO
Data Warehousing Intern
January 2014 – June 2014
Completed a semester-long internship at a manufacturing company. Developed skills in data mining, data warehousing and cleansing, and using data modeling software.
Udemy Open Source Educational Center
Master’s Certificate: Data Science
University of Missouri, Rolla
Bachelor of Science: Information Technology
Minor: Healthcare Informatics
Final Tip: Give Your Resume a Final “Test”
Before you send out your resume, take one last look at it. In particular, make sure that it ticks all the following boxes:
- Use relevant keywords, taken from the job description.
- Tailor the language of your resume for the specific job you are applying for.
- Quantify your claims with data that proves your ability to get results.
Good luck with your application!