Data Scientists are Really Just Product Managers. Here’s Why.

Matt Przybyla
Sep 10, 2021

Data Scientists are Really Just Product Managers. Here’s Why.

Sep 10, 2021 4 minutes read

Unpopular opinion?

Table of Contents

  1. Introduction
  2. Business and Product Understanding
  3. Stakeholder Collaboration
  4. Summary
  5. References


As mentioned above, the title of this article may be an unpopular opinion, but let me lay it out for you to see what you think with a new perspective. If you are in school still, this statement might sound quite surprising, however, if have been in the tech business for a few years, this statement may come as no surprise to you. Of course, this statement will not be true for everyone, all of the time, but it gets pretty close when you point out the similarities between these two product roles. With that being said, I will outline some of the similarities between data science and product manager roles, skills required, and goals below.

Business and Product Understanding

Photo by Hugo Rocha on Unsplash [2].

When you work as a data scientist, it is essential that you know the business, its goals, as well as its shortcomings, the same can be said about product managers. The main difference between these roles is the method by which their specific goals are reached, but overall, the main goals are shared. Here is an example:

Data Science Goal:
  • Identify problems in the product
  • Use data science models as a solution to a product problem
  • Use data science models as a product
  • Analyze data to predict future data with algorithms

Product Manager Goal:
  • Identify problems in the product
  • Rank which problems are of most concern
  • Look into data to learn about future data trends

Of course, data science can have a focus on coding, but without an understanding of the business and product, a data science model can be completely useless. It is essential to have this understanding for both roles, as this knowledge is how you come up with next steps, a process, problem diagnosis, and eventual solutions.

On the company structure level, you will see that data scientists are often the bridge between departments or a part of both engineering and product. That statement alone can show that there is considerable overlap.

Here are some skills that both roles share:
  • Data exploration
  • Problem diagnosis
  • Visualization tools (Tableau, Looker, Lucidchart, etc.)
  • Querying (SQL)

In addition to some of the skills shared between roles, there is also a similar process:
  • Product problem isolation or product improvement
  • Data analysis
  • Current process analysis
  • Solutions (this is where data science differs by being the ones who will create the model, product managers will organize this step, with things like results, costs, timeline, and how it will ultimately affect the business, but data scientists can also share some of that work)
  • Results presentation
  • Testing
  • Executive approval/approval in general
  • Implementation

As you can see, some skills, process steps, and data science and product management goals are shared. Sometimes, there are no product managers at smaller companies, and therefore, data scientists will have to work that role as well.

Stakeholder Collaboration

Photo by Mimi Thian on Unsplash [3].

When you work as a data scientist, you will have to collaborate with several verticals of the business and their respective stakeholders. The same can be said for product managers. Both data scientists and product managers can also be stakeholders themselves.

Here is where these roles share stakeholder collaboration:
  • Proof of concepts with software engineers, data analysts, and executives, etc.
  • Level of effort analysis with the same roles from above, and more
  • Setting up meetings with those roles
  • Updating those roles on steps
  • Allocating work to others

Overall, both data scientists and product managers can prove to be cross-functional in their work, as well as in who they collaborate with, whether that be a data analyst, salesperson, or software engineer (etc.).


The goal of this article is not to say one role is better than another, but to highlight that both roles have a considerable amount of overlap in their daily tasks, skills required, who they work with, and overall goals. To be more specific, maybe data scientists are just product managers who have special skills and focus on algorithms.

To summarize, here are some ways that data scientists and product managers are similar:
* Business and Product Understanding
* Stakeholder Collaboration

I hope you found my article both interesting and useful. Please feel free to comment down below if you agree or disagree with these comparisons between roles. Why or why not? What other comparisons (or differences) do you think are important to point out? These can certainly be clarified even further, but I hope I was able to shed some light on some of the common similarities between data scientists and product managers. Thank you for reading!

I am not affiliated with any of these companies.

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