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
    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
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Are Data Scientists Overpaid?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Culture/Leadership > Are Data Scientists Overpaid?
Big DataCulture/LeadershipData MiningInside CompaniesMarket Research

Are Data Scientists Overpaid?

vincentg64
vincentg64
4 Min Read
SHARE

data scientists

data scientists

(This post is a response to “Are Data Scientists Overpaid?” – ed. note)
The answer? Fake data scientists are overpaid, real ones underpaid.
Read Fake Data Science and Horizontal vs. Vertical Data Scientist. Many real data scientists are actually unemployed and can’t find a job. The number of applicants per job ad ranges from 20 to 500 – you can check these numbers yourself on LinkedIn, entering the keyword “data science” in the “Job Search” box (top right corner, select “Jobs” as search criterion).
In my case, as a data scientist, I generate leads for marketers. A good quality lead is worth $40. The costs associated with producing one lead is $10. It requires data science to efficiently generate a large number of highly relevant leads, purchasing the right traffic, organic growth optimization etc. If I can’t generate at least 10,000 leads a year, nobody will buy due to low volume. If my leads don’t convert in actual revenue and produce ROI for the client, nobody will buy. 
Also, thanks to data science, I can sell leads for a lower price than competitors – much less than $40. For instance our newsletter open rate went from 8% to 24%, significantly boosting revenue and lowering costs. We also reduced churn to a point where we actually grow, all of this thanks to data science. Among the techniques used: improving user, client and content segmentation; optimizing delivery rate from an engineering point of view, eliminating inactive members, detecting and killing spammers, and optimizing a very various mix of newsletter metrics (keywords in subject line, HTML code, content blend, ratio of commercial vs. organic content, keyword variance to avoid burn out, first sentence in each message, levers associated with re-tweets, word-of-mouth and going viral, etc.) to increase total clicks, leads and conversions delivered to clients. Also, we need to predict sales and revenues – another data science exercise.
Am I overpaid if I can deliver the leads with a higher margin and lower price? No, I’m just smarter than competition. I’ve also developed a business model that is not subject to click fraud, thus avoiding losses and litigation. At the end of the year, my revenue after cost is far above the $133k mentioned by ZDNet, yet I don’t feel overpaid, and my clients don’t feel that our service is expensive – if they did they would stop working with us.
Rule of thumb: You are overpaid if your company makes less than 3 times your salary, from your work. No matter how much or little you are paid. By making money, I mean revenue generation or cost savings. By revenue, I mean extra money resulting e.g. from optimizing ad campaigns. Not always easy to measure the financial lift that an employee brings to a company.
TAGGED:business intelligenceData ScienceData Scientist
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

revolutionising our social visibility
Artificial Intelligence

How Data Science Is Revolutionising Our Social Visibility

12 Min Read
google nexus BI lesson
Uncategorized

4 Retail BI Lessons to Learn from Google’s Nexus Fail

5 Min Read

Big Data: What can an energy company teach us about data science?

7 Min Read
mobile intelligence
Artificial Intelligence

How is Mobile Intelligence Reshaping the Marketing Industry?

7 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 and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
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?