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
    data analytics in ecommerce
    Analytics Technology Drives Conversions for Your eCommerce Site
    5 Min Read
    CRM Analytics
    CRM Analytics Helps Content Creators Develop an Edge in a Saturated Market
    5 Min Read
    data analytics and commerce media
    Leveraging Commerce Media & Data Analytics in Ecommerce
    8 Min Read
    big data in healthcare
    Leveraging Big Data and Analytics to Enhance Patient-Centered Care
    5 Min Read
    instagram visibility
    Data Analytics Plays a Key Role in Improving Instagram Visibility
    7 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: 4 Crucial Qualifications Data Scientists Need to Thrive
Share
Notification Show More
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 > 4 Crucial Qualifications Data Scientists Need to Thrive
Data Science

4 Crucial Qualifications Data Scientists Need to Thrive

Ryan Ayers
Ryan Ayers
5 Min Read
lessons learn from data scientists
Shutterstock Licensed Photo - By weedezign
SHARE

Data scientists have a prominent job. They are essential to every industry and just about everyone who loves data wants their job. Sometimes, they seem like magicians. When you pull back the curtain, of course, they’re just people—very smart people. If you’re feeling stuck in your career, take these four lessons from leading data scientists so that one day, you can get a job as a data scientist.

Contents
1. Failure Shouldn’t Be Feared2. Don’t Be Afraid to Go Back to School3. Stay Driven4. Learn to Leverage the Unlimited Potential of Data

1. Failure Shouldn’t Be Feared

It’s an interesting paradox: just about all of us fear failure. At the same time, failure is the best teacher and is often inevitable to our future success.  João Marcos Gris failed many times when he first tried to land a data science role after getting a BSc degree in Computer Engineering. Getting turned down (failing) taught him to seek feedback and learn from failure to ultimately get the results he wanted. His thoughts on the process:

“I really felt that this experience was very enriching for me, despite being a very tiring one also. I’ve made a lot of mistakes along the way and tried to improve myself for each and every one of the applications that I did.”

Turning your failures into learning experiences is the only way to grow and achieve your goals.

2. Don’t Be Afraid to Go Back to School

Steve Mills of Booz Allen Hamilton notes that being a data scientist isn’t just about crunching the numbers. He emphasizes the need to think creatively and artistically, even in a highly mathematical and analytical field like data science. Data scientists, Mills says, “aren’t just computer nerds.” They need to have communications, curiosity and creativity. Sometimes, cultivating that creativity takes a little nudge.

More Read

The Problem with Investing Based on Pattern Recognition

Navigating The Big Data ICT Training Process In The UK
Managing Data Scientists
How People from Outside of the Tech Industry are Breaking into Data Science
New Research on Big Data

If you feel like you’re stuck in a rut, it may be time to think about reinvesting in your education. If you’ve always been logical, try some creative classes. Explore a new career. Going back to school may help you expand your knowledge and thinking, give you a new perspective, specialize your skills, improve your resume, develop a larger network, and advance your career.

3. Stay Driven

 It’s not always easy to keep up motivation when you’re tired or discouraged. The journey doesn’t stop when you reach your ideal job, however. You need to stay humble and driven—always asking the next question and pushing yourself to be better. The world doesn’t stand still, and neither should you—you should always be seeking knowledge from others and adapting to the world around you.

Bill Schmarzo says that one of the first skills he looks for when hiring data scientists is humility. It is even more important than skill. He knows that people who maintain humility work better in teams and are always going to stay driven, trying to constantly improve themselves and their work. He also sees it as the biggest factor in creating a strong hypothesis—absolutely crucial for data scientists.

4. Learn to Leverage the Unlimited Potential of Data

 Former Chief Data Officer DJ Patil  has jumped around from a number of positions ranging from LinkedIn to Ebay to professor to government official—all thanks to both the rise of data and his ability to leverage its potential to create new opportunities.

He also has a remarkable ability to discover innovative solutions to problems. During his first year as a graduate student, he asked administrators for access to the computer lab (off-limits then to first-year grad students). They denied his request, but he was determined. So he went straight to one of the professors and asked how he might get computer access. The man who would become his mentor gave him a note, and the administrators reluctantly granted him access to the computer lab.

It’s clear that Patil has used that approach of applying creative solutions to nearly everything he does. You need creativity and drive to leverage the nearly unlimited power of data. Today, we’re seeing just how powerful it can be in almost every sector even criminal justice. No matter what your ideal career path may be, there’s almost certainly some way to use data to your advantage—you just can’t take no for an answer.

TAGGED:Data Sciencedata scientistspersonal growth
Share This Article
Facebook Twitter Pinterest LinkedIn
Share
By Ryan Ayers
Follow:
Ryan Ayers has consulted a number of Fortune 500 companies within multiple industries including information technology and big data. After earning his MBA in 2010, Ayers also began working with start-up companies and aspiring entrepreneurs, with a keen focus on data collection and analysis.

Follow us on Facebook

Latest News

AI for MSPs
Autotask and ConnectWise Prove the Benefits of AI in IT
Artificial Intelligence Exclusive
gamer laptops
Data-Driven Tips to Choose the Perfect Gamer Laptop
Best Practices Reviews
smart crosswalk
AI Reduces Pedestrian Collisions With Smart Crosswalks
Artificial Intelligence Exclusive News
ai success
How Leaders Can Unlock AI’s Full Potential for Business Success
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

programming concepts for data scientists
Big DataData ScienceExclusiveProgramming

Crucial Programming Concepts For Data Scientists

6 Min Read
data science applications
Data Science

C and C++ Are Surprisingly Useful for Data Science Applications

5 Min Read
Data Scientists
Data Science

Here’s Why a Bootcamp Won’t Make You a Data Scientist

5 Min Read
using docker for data science
Data Science

Top Benefits of Using Docker for Data Science

8 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 in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-24 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?