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
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: 4 Crucial Qualifications Data Scientists Need to Thrive
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 > 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 Feared
  • 2. Don’t Be Afraid to Go Back to School
  • 3. Stay Driven
  • 4. 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

data science in scheduling solutions
Data Science Offers Fascinating New Scheduling Solutions
Why AI Cannot Survive Without Big Data
It’s a Bird! It’s a Plane! No, It’s Just a Data Scientist.
A Strained Data Science Analogy
How Data Science Is Revolutionising Our Social Visibility

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 Pinterest LinkedIn
Share
ByRyan 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 in business
Recurring Revenue Strategies for the AI Business Era
Artificial Intelligence Exclusive
ai for playground safety
Using Data to Plan Safer, More Efficient Public Playgrounds
Big Data Exclusive
AI for cybersecurity
How AI Supports Modern Penetration Testing
Artificial Intelligence Exclusive
ai kids and their parents
How Cities Use AI to Improve Playground Design
Exclusive News

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

data scientist
AnalyticsBig DataBusiness IntelligenceJobs

Data Scientist Scarcity: Automation Is the Answer

5 Min Read
Mok Oh new venture in big data
Big Data

Mok Oh’s New Big Data Venture

7 Min Read
Hadoop vs Spark
Big DataHadoopMapReduceProgramming

Big Data New Age: Hadoop vs Spark

5 Min Read

The Problem with Investing Based on Pattern Recognition

4 Min Read

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

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

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

Sign in to your account

Username or Email Address
Password

Lost your password?