Data Scientist vs Machine Learning Scientist Difference | Towards Data Science

IntroductionData ScientistsMachine Learning ScientistsSummaryReferences
Introduction
Data Scientists
Machine Learning Scientists
Summary
References
These two roles can sometimes be interchangeable amongst recruiters, however, if you are specialized in either of these roles, you know there is a difference. Both roles share a focus on machine learning algorithms, yet their day-to-day can be very different. Data scientists tend to focus more on use cases like credit card fraud detection, product classification, or customer segmentation, whereas machine learning scientists focus on use cases like signal processing, object detection, automobile/self-driving, and robotics. Below, I will be describing more specific differences between data scientists and machine learning scientists in terms of job goals, dedication, and skills.
Data scientists may see more consistent job descriptions along with their respective education and skills required. A typical data scientist will usually work with a stakeholder to define a problem, build a dataset, compare various machine learning algorithms, output results, and interpret and present those results. Data scientist roles have a focus on business and collaboration between stakeholders. The models they build tend to not take as long as a machine learning scientist, say around a few months or even a few weeks, depending on the project.
Here are some of the education and skills you can expect as a data scientist:
Education
BS or MS degree oriented
Data Science
Statistics
Business Analytics
Skills
Python or R
Data Analysis
Tableau or another visualization software
Jupyter Notebook
SQL
Regression
Model Building
Tend to be more simple use cases like ad-hoc classification, time series analysis, etc.
Data scientists usually will have a foundation in business or data analytics, and then they will be able to use code, usually in Python or R to automate predictions using machine learning libraries in those programming languages.
The road to a data scientist or machine learning scientist position may be different as well. For example, perhaps a data scientist started off as a statistician, business analyst, data analyst, or business intelligence analyst, and then became a data scientist. For a machine learning scientist, it may be a path where you start off as a computer scientist, software engineer, physicist, robotics engineer, or engineer in general, and then become a machine learning scientist. Of course, the typical path is not required, and you can land one of these positions in your own way, keeping in mind your own personal goals of what you want to do with machine learning.
While data scientists can focus more on building a model and presenting results to stakeholders, machine learning scientists often are more focused on the algorithms themselves, as well as the software engineering around implementing the model. Machine learning scientists often have the word ‘Research’ in their title as well. This means that you may focus more on researching algorithms in general before implementing a more simple approach. Overall, these roles can indeed be the same at different companies, so it is ultimately up to you to realize the difference whenever you look at a job description. The biggest takeaway is that data science roles seem to be more popular and more consistent, meaning they do not vary as much in their job description as much as machine learning scientists do, so take these skills with a grain of salt.
Some of the differences are in the education and skills required of which I will note below:
Education
Ph.D. degree oriented
Machine Learning
Computer Science
Robotics
Physics
Mathematics
Skills
Research-heavy
Signals & Distributed Systems
OpenCV
C++ or C
Quality Assurance
Automation
Model Deployment
Unix
Artificial Intellgence
Tend to be more complex use cases like self-driving cars, automatic robotics, etc.
The skills required for machine learning scientists tend to include more software engineering focus, like C++ for example, as well as more automation and deployment focused. Also, in some job descriptions, we will see that there might be a specialization like Physics or Robotics.
This article has outlined some of the differences and similarities between these two roles. There is a bit of overlap, as well as some clearer differences. I wanted to post this article as well in hopes that people will comment on their experiences in either role, as I know these two roles to some companies and employees may be exactly the same or vastly different. I have personally seen these differences myself, however, that does not mean that the same will be true for you. With that being said, I encourage you to explore both positions — in not just articles, but also in job descriptions themselves as that is where you will get the most accurate and applicable information, especially per company.
To summarize, here are the main differences between data scientists and machine learning scientists:
* Data scientists: Python, R, statistics, visualization tools, perhaps faster paced, simpler use cases* Machine learning scientists: software engineering, research-focused, perhaps slower paced, more involved use cases
I have also attached some real job descriptions [4, 5, 6] if you would like to see machine learning scientist examples, as I know those positions tend to be rarer. It will also allow you to see the differences yourself.
I hope you found my article both interesting and useful. Please feel free to comment down below what you see as similarities or differences between these two positions. Comment down below if you disagree or agree with these differences between data scientists and machine learning scientists.
Please feel free to check out my profile and other articles, as well as reach out to me on LinkedIn. I am not affiliated with any of the mentioned companies.
[1] Photo by Fitore F on Unsplash, (2019)
[2] Photo by Stephen Dawson on Unsplash, (2018)
[3] Photo by Bram Van Oost on Unsplash, (2019)
[4] Indeed, Machine Learning Scientist / Engineer (MLSys 2021) Job Description, (2021)
[5] Indeed, Machine Learning Research Scientist Job Description, (2021)
[6] Indeed, Machine Learning Scientist Job Description, (2021)