Data Science In Marketing – How Much It’s Worth And Where To Get Trained

Lillian Pierson, P.E.

Lillian Pierson, P.E.

Reading Time: 9 minutes

[UPDATED: April 2022] When you think of marketing teams, the usual suspects probably come to mind. Developers and designers, copywriters, marketing strategists, and social media managers. But the hottest new role marketing departments are looking to fill is one you’re maybe not quite as familiar with. I mean, how much do you really know about data science in marketing?

That role is a Marketing Data Scientist, my friend. 

No I’m dead serious, here!


For example, last week, my coaching client name Rho Lall reported that he used my business coaching curriculum to land a data contract in “digital advertising” – and got a 40% pay bump in the process.

And 2 weeks before that… a different coaching client, Kam Lee, reported using my program to land a $96k data services contract in “revenue optimization”.

If you’d like to hear the updated success story of marketing data scientist, Kam Lee, you can do so here.

If you are an analytical-minded marketing professional and looking for a place to specialize – Marketing Data Science is HOTaf at the moment…

I’ll say it again… If you’re a data-savvy marketer, or a bit of an marketing analytics nerd, searching for their next big career move. The field of data science in marketing has your name written ALL over it.

And if you’re more of a scanner than a reader, use the links to speedboat your way to the juiciest parts of this blog:

#1 Marketing Data Analyst vs Marketing Data Scientist (Skills & Requirements)

#2 Where to get trained to do Marketing Data Science

#3 Why companies pay almost twice as much for Marketing Data Scientists


Look, if you’re currently working in a marketing analytics capacity and make the transition towards marketing data science, you could quickly start making 30% more than your current salary.

Now I know what you may be thinking…”Lillian, that sounds nice and everything but wouldn’t I need to go back to school? Or take a bunch of fancy-pants, super-duper expensive trainings?”

And my answer to that question is NO! I’m going to be showing you how to pivot your career and hop aboard the marketing data science train to increase your current earning capacity by 30% with just a couple of books and online courses. Are you ready?!


A little bit of backstory

I started thinking about this exciting field when I found a message in my LinkedIn inbox from a recruiter looking to interview me for a Marketing Data Scientist position that she was trying to fill. The location was all wrong for me, but the email really got me thinking about data science in marketing, and what it was about my LinkedIn profile that had piqued her interest.

It’s clear I have the data science background. After all, I’ve trained >1.3 MM data professionals over on LinkedIn, and here at Data-Mania we’ve supported 10% of Fortune 500 companies. Combined with my experience growing my communities (we now have over 650,000 of you across LinkedIn, Instagram, and Twitter), as well as running the day-to-day marketing operations of my data business, I can understand why she thought I might be a good fit.

But despite my familiarity with both marketing AND data science, I still had a few questions. What exactly IS “Marketing Data Science?” What sort of work do Marketing Data Scientists do? Does the role pay well? And What is the difference between a Marketing Data Analyst and a Marketing Data Scientist?

The whole exchange between me and the recruiter got me excited about this new area of data science and what exactly it’s all about. Today, you’re going to get the complete run-down on data science in marketing, and how you can get started in this fascinating and profitable niche. Make sure to stick around until the end to learn about the best (affordable!) resources to start up-leveling your skillset, so you can get the career recognition and pay raise you’ve been craving.


What’s the difference between a “Marketing Data Analyst” & a “Marketing Data Scientist”?

First things first…what exactly is a Marketing Data Analyst?

The role of Marketing Data Analyst is very similar to that of Business Analyst, except that their efforts are focused solely on marketing initiatives. Moreover, they collect and analyze both internal and external datasets, and then use the information to help them strategically plan and implement marketing initiatives for their organization.

They often produce descriptive and diagnostic insights based on basic data monitoring and trend analysis, and focus heavily on market research and planning. The technical skills required to be a Marketing Data Analyst are usually Excel, SQL, and perhaps SAS. In the United States, the average salary for a mid-level Marketing Analyst is $86,744/year (according to Glassdoor, 2022).

What about Marketing Data Scientists? 

On the other hand, marketing data scientists focus exclusively on improving organizational marketing effectiveness. By analyzing both internal and external datasets, these strategic professionals help their organizations to better understand their customers, as well as advise on modifications or additions to marketing tactics and analysis methodologies. 

Their main job? Producing reliable predictive and prescriptive insights, based on advanced statistical modeling and/or machine learning methodologies. And while the nature of the marketing data scientist role is technical, it’s impossible to thrive in this role without seasoned soft skills – being able to communicate complex ideas in simple terms is crucial to management understanding and benefiting from the work they do. 

In the United States, the average salary for a Marketing Data Scientist is $112,502/year (according to Glassdoor, 2022). More about the role, skill requirements, and background requirements are listed below. 

Job Role of a Marketing Data Scientist:

  • Generate prescriptive insights – tactical and strategic insights to improve marketing effectiveness
  • Exploratory data analysis
  • Metric and method selection
  • A/B testing
  • Advising, training, and assisting management and other professionals in working with and understanding organizational data

Required Skills of a Marketing Data Scientist:

  • SQL
  • Data visualization (Tableau, D3.js, etc.)
  • Machine learning in Python or R
  • Great “people skills” – to collaborate with data engineers, business management, and other support personnel

Educational and Professional Background of a Marketing Data Scientist:

  • A university degree in a quantitative field of study
  • Internet marketing experience
  • Business analytics experience


Data Science in Marketing: Where to Get Trained…

Has getting started in marketing data science piqued your interest? If you’re looking to get trained in this exciting new field, I have a variety of resources for you, depending on how you like to learn best!

For certain technical skills, such as Python or SQL, many learners find they prefer watching a video to easily see certain concepts visualized. If this is you, an online course might be your best bet. For other, more theoretical skills, you might want to cozy up with a book and take some notes! No matter which way you prefer to learn, here are some incredible resources to get you well on your way to becoming a marketing data scientist.

Looking for a high-level overview of data science? My book, Data Science For Dummies, will bring you up to speed!

data science in marketingLearn SQL

  • The Complete SQL Bootcamp 2020: Go from Zero to Hero
    This comprehensive course is taught by Jose Portilla, who currently serves as Head of Data Science at Pierian Data Inc. Jose has taught thousands of students in this beginner-friendly course. This course features video lectures, challenges, assessments, and a certificate of completion. Also, it includes a lifetime access to a community of students and discussion forums.
  • The Ultimate MySQL Bootcamp: Go from SQL Beginner to Expert
    This course is led by Colt Steele. Colt is a developer passionate about teaching, most recently serving Lead Instructor and Curriculum Director at Galvanize SF (where, after graduating, 94% of his students went on to receive full-time developer roles!). In this engaging course, you’ll model real-world data and generate reports using SQL – you’ll even get a chance to clone the database structure of Instagram! 

Learn Data Visualization (Tableau, D3.js, etc.)

Some books that I can recommend for digging deeper into how to implement marketing data science include:

And as far as online courses are concerned, these will help get you started:

  • Tableau 2020 A-Z:Hands-On Tableau Training For Data Science
    This Tableau course is taught by Data Science management consultant Kirill Eremenko and is a wonderful starting point for anyone looking to get started with data visualization. From the very first lesson, you’ll already be able to start analyzing data using Tableau. From there you’ll go on to learn about bar charts, line charts, area charts, maps, story lines and more!
  • D3.js Data Visualization Fundamentals – Hands On
    Learn how to build stunning data visualizations in this course by New Horizon, a learning company that aggregates training materials from various tutors and provides a hand-picked, curated set of courses. This course has a 4.8-star rating and provides a practical hands on approach to learning the D3 library.

Learn Data Cleaning and Modeling in Python

    • [My course on building recommendation systems] Building A Recommendation System With Python
    • Python for Data Science Essential Training Part 1
      In my Python Essential Training course on LinkedIn Learning, I take you step by step through a practical data science project: a web scraper that downloads and analyzes data from the web. You’ll learn techniques to clean, reformat, transform, and describe raw data. Additionally, you’ll learn to generate visualizations; remove outliers; perform simple data analysis; and generate interactive graphs using the Plotly library.
    • Python for Data Science Essential Training Part 2
      In my follow-up part two for intermediate Python learners, I walk you through a second data science project: building machine learning models that can generate predictions and recommendations and automate routine tasks. You’ll learn how to perform linear and logistic regression. Also, you’ll learn to use K-means and hierarchical clustering, and identify relationships between variables. Finally, you’ll know how to use other machine learning tools such as neural networks and Bayesian models.
    • Data Science For Dummies Chapter 4: Math, Probability, and Statistical Modeling + Chapter 11: Making Marketing Improvements (with data): You may be a little overly niched-down with your current data expertise (and don’t know much about how things work in other aspects of the field, like marketing data science, data strategy, data startups, data engineering, etc). This book serves as an easy access handbook in cases where you need to orient yourself on these topics FAST!

Develop Your People Skills

As a data marketing scientist, you’ll need great interpersonal skills. This is needed to collaborate with data engineers, business management, and other support personnel. Places you can go to start:

  • Dare To Lead By Brene Brown [BOOK]
    This should be required reading for anyone that ever wants a leadership position, but it’s seriously helpful for anyone working with others. Brene teaches us what it takes to be a strong, courageous leader who creates a BIG impact in the world.
  • Winning With Data: 30 Day Challenge [PRODUCT]
    Ready to double your salary without the downtime of taking yet more coding courses? Winning With Data is a 30-day challenge & digital asset bundle that dramatically shortcuts the path to becoming a highly-regarded data leader, even if you don’t have a decade of data implementation experience. Join Winning With Data now and start taking decisive action to become a better data leader TODAY!


Why would an organization want to pay 30% more?

With a mid-level Marketing Data Scientist’s salary currently costing a hefty $112,502/year (source: Glassdoor, 2022) – which is ~30% more than the average salary of mid-level Marketing Analyst (source: Glassdoor, 2022). While neither of these salaries are something to scoff at, you may be wondering – why would an organization want to pay more to equip its marketing team with its very own designated data scientist? 

The answer is simple.

The predictive and prescriptive insights generated through marketing data science can and DO have the capacity to increase the maximum earning potential of today’s businesses. In fact, these businesses are those that may have otherwise remained in a competitive standstill for years to come. Data science is a powerful tool that marketing departments looking to increase profits simply can’t ignore. And, they’re willing to shell out the sizable salary needed to reap the benefits.

What about YOU?

Have you been considering making a career transition into data science? What is most exciting to you about the field? Next, what factors have kept you hesitating? Fourth, what are your thoughts on the use of data science in marketing? What type of data science is most of interest to you? I’m always looking to chat with my readers. I wanna hear more about what kind of resources and content they’re looking for. Come say hi using the chat button in the corner of the site! Tell me what you want to learn next!

More free resources that'll help...

Get The Badass's Guide To Breaking Into Data

I was working a 9-to-5 as a data analytics developer back in 2012 when I started Data-Mania. With that transition, the seed was planted to write an ebook that helps other people break into the field that'd been so generous to me. You can’t keep something like this to yourself, right? 😉 Today we’ve published this free ebook, and it's helped thousands of people just like you make the transition....

Take The Data Superhero Quiz

You can take a much more direct path to the top once you understand how to leverage your skillsets, your talents, your personality and your passions in order to serve in a capacity where you’ll thrive. That’s why I’m encouraging you to take the data superhero quiz.

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This Post Has 26 Comments

  1. Julio Rodriguez-Martino

    Very nice summary! Makes me want to dive right into this world. Thank you for your clear and concise description.

  2. Rishi

    The article is awesome. I am pursuing Data Science and was looking for specific domain concentration within Data Science.

  3. Branka Budja

    Hi, thanks for the text is very usfull for me. Please advise which course is the best for data sciencis in marketing for FMCG and retail. Thanks in advance

  4. Anonymous

    thanks a lot!

  5. Paul Raja

    The difference between the two is really stark no wonder the difference in skills and salary. The only challenge though is for the ability of the senior managers to be able to actually understand the additional value the data scientists bring. This is obvious in the performance of the company. Those who analyse and understand this more like the Amazons of our time grow very quickly the rest just stagnate or stare helplessly at a falling customer base.

  6. owenmorris

    Thanks a lot very much for the high quality and results-oriented help. I won’t think twice to endorse your blog post to anybody who wants and needs support about this area.

  7. Mike Ko

    Thank you so much for the article, it’s very aspiring. Currently, I’m working as Senior PPC Specialist and wants to move into Marketing Data Science position, any resource would you recommend I study for to required that position? Anything would be really helpful, even your courses too. Thanks

  8. Mohammad

    Thanks a lot for this article! I enjoyed reading it.

    Right now I am into digital and offline marketing and market research. Would learning data science help me as a soloperuneur?

  9. Ali

    Great article. Pretty neat and clear.

    I’m in to online marketing and sales. I have done bachelor’s in business administration majored in marketing.

    Deriving meaningful insights we’re my thing from the that do you think Data science in marketing can help me in realigning my career.

    I have no previous experience with programming.

  10. Matteo

    Great Article. Data Analysis as asset value is something that is really interesting for effective decision making. Knowing python, Tableu and SQL I see how data computation is useful to resolve business problem. Do you have any interesting business case about Data Science application on Marketing Problems? Both kernel and report?

    Your page is really cool, Lilian. Also the pdf about Breaking into Data

    1. Lillian Pierson, P.E.

      Thanks for your kind comment, Matteo! I absolutely have use cases on this topic, most of which are included in my course (ie; not on the blog). Look into what AIMIA is up to

  11. Evelin

    hi! Very helpful this article. I am leading a Marketing Team of a financial services company. We have a business insight team, but they don´t prioritize our requirements because many other priorities oriented more to hard finance come up first. Now that I have an open position to fill out, instead of recruiting a Marketing Analyst that does 80% of their time BAU marketing comms, and 5% data analysis, I wanted to build this analysis position into my area, and kind of outsource comms building, I now we can provide the business much more added value this way then, how we used. Of course, I am not academically formed to guide a Data Scientist, and want to take full advantage of this more Marketing oriented position. Would you recommend to move foward this way? Thanks a lot!

    1. Hi Evelin – Thanks for reaching out. Someone from our team will be in touch with you shortly.

  12. Liz

    Hi. Thank you for the great post and answering questions I had before even asking! This is an area that is growing and one with fantastic value and opportunity. I have a similar question to that of Evelin. I too lead a marketing team and we have an open position. I am very interested in considering a marketing data scientist role as this is a missing skill set on the team. I though am not well versed in this either and want to effectively guide and support this person. One other question building on the description of this role being a great communicator as noted in your post, for smaller organizations, have you seen a data scientist combine with content marketing or writing?

    1. Lillian Pierson, P.E.

      Thanks! So glad it is helpful! “data scientist combine with content marketing” – I did that myself – that’s one way I ended up building out my brand so quickly. It’s a very effective strategy if done properly. I’d love to answer your questions further inside the Data Strategy Club, if you care to join? >>

  13. Rebecca

    Thank you for the amazing article which provides me with helpful points I need as an undergrad student. I am currently a Marketing freshman who is considering being a Marketing Data Scientist. I wonder if I can stay in this Marketing track and steer to a data science focus or just switch to be a Data Science major and take minor Marketing courses. I hope it makes sense. Which path do you think is more ideal?

  14. Jess A

    Is it difficult to transition from a digital marketing analyst to a Marketing data scientist ? Please inform me accordingly. Is it better to be a general data analyst then transition.

    1. Lillian Pierson, P.E.

      No – it shouldn’t be depending on your background. You need to look at the job postings and see what skills you are missing still.

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