Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Writing the Ideal Resume for Your Next Job in Data Science
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Science > Writing the Ideal Resume for Your Next Job in Data Science
Big DataData ScienceExclusiveJobs

Writing the Ideal Resume for Your Next Job in Data Science

The right resume can do wonders to help you land a great job as a data scientist.

Philip Piletic
Philip Piletic
6 Min Read
data science jobs
Shutterstock Licensed Photo - By Wright Studio | stock photo ID: 1247255884
SHARE

While it might sound ironic that high-tech fields such as data science still require you to submit a resume, even the most cursory look over a list of job openings should prove this to be true. Managers and HR department staffers in even the most technically-oriented companies are actually on the lookout for candidates with an impressive resume. This might encourage some applicants to stretch the truth.

Contents
Why Truth is So Important in Data Science ResumesFormatting Your Resume in the Preferred WayBalancing History with the Present

If you’re applying for a job in the IT or data science spaces, then you don’t want to do this. Consider adding statistics and other data points about your previous job, even if you don’t have exact numbers. This will give you the freedom to promote yourself as an expert without ever suggesting something that’s untrue.

Why Truth is So Important in Data Science Resumes

Human resources directors might not be directly related to the technology resources of most of the firms they represent, but that doesn’t mean they can’t leverage the same tools everyone else in said firms rely on. That means they’ll spot a lie, so you want to go over everything in your resume to make sure you were telling the truth.

That being said, the ideal length of a resume is somewhere around 475-600 words, so you shouldn’t feel like you’re under any pressure to put filler in there. Short and sweet rules the day, especially when you think about how many resumes some reviewers have to look through a day. While apps are indeed used to automatically process resumes and prevent any personal biases from leaking into the review process, the final decisions are still made by humans at even the leading data science firms.

More Read

Stuck in First Gear
Big Data and the Myth of Consumer Control
4 Ways that Data Analytics Can Boost Performance by Improving Employee Handbooks
Conversation with Eric Siegel on Predictive Analytics World
Data Visualization: How (2 of 2)

As a result, you want to be concise as well as truthful. Perhaps most importantly, you want to present your information in a way that makes sense for the type of job you’re applying for.

Formatting Your Resume in the Preferred Way

Relatively few companies use automated resume application processes for professional employees. These are generally deployed only at facilities that expect a large degree of turnover, such as a retail operation. Anyone who is applying for a professional-level career at a place that manages large amounts of information is more than likely going to need to submit an old-fashioned resume.

A growing number of companies are actually asking potential hires to submit their resumes as traditional flat text files, which should be editable with almost any piece of software. Considering that computer professionals tend to be evenly split when it comes to GNU/Linux, Windows and Mac platform face-offs, this is pretty good news. Creating a resume that meets these requirements could be as easy as firing up your favorite notepad application and typing away.

Other organizations are starting to rely more heavily on the Roman Executive format, which first rose to prominence in the legal profession within the last decade or two. This may require you to be more careful when it comes to what sections you include, but you still won’t want to get carried away with employment history.

In fact, some observers feel that industry insiders now care more about skills than they do about the places that you may have worked in the past.

Balancing History with the Present

Chances are that you’ve worked several jobs in the past that don’t have anything to do with the IT or data science fields. While you might want to include these if they’re particularly impressive, you don’t need to write a complete employment history that stretches all the way back to your summer job during high school. Instead, you might want to narrow things down to jobs that show you have a background in data analytics.

You’ll certainly want to include any relevant educational experience or professional certifications that you might have, but more employers these days are probably looking for proof that you know how to do the kind of job that you’re applying for. Consider adding a dedicated technical skills section that spells out all of your various competencies.

While you don’t want to brag or sound shamelessly self-promotional, you should be honest about any area that you personally feel you excel in. Potential employers will expect that you’re able to do anything you put on this list, so be honest, but don’t be afraid to show yourself in the best possible light.

Once you’re done, read things over a few times before you finally submit your resume. Taking a little extra time to proofread can help you catch errors you might not otherwise have found.

TAGGED:big dataData Sciencedata science jobs
Share This Article
Facebook Pinterest LinkedIn
Share
ByPhilip Piletic
Follow:
My primary focus is a fusion of technology, small business, and marketing. I’m a writer, marketing consultant and guest author at several authority websites. In love with startups, the latest tech trends and helping others get their ideas off the ground. You can find me on LinkedIn.

Follow us on Facebook

Latest News

sales and data analytics
How Data Analytics Improves Lead Management and Sales Results
Analytics Big Data Exclusive
ai in marketing
How AI and Smart Platforms Improve Email Marketing
Artificial Intelligence Exclusive Marketing
AI Document Verification for Legal Firms: Importance & Top Tools
AI Document Verification for Legal Firms: Importance & Top Tools
Artificial Intelligence Exclusive
AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

The Problem with Investing Based on Pattern Recognition

4 Min Read

Tips To Get Your Organization Ready For Big Data

5 Min Read
big data strategies
Big Data

5 Crucial Database Practices For Overseeing Sound Big Data Strategies

6 Min Read
big data helping students
Big DataExclusiveFintech

Big Data Yields Important Insights On Student Loan Forgiveness

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?