Data Scientist and Machine Learning Engineer are two popular jobs in the tech industry in 2024. According to statista.com, the market is estimated to have an annual growth of 36.07% from 2024 to 2030. Moreover, experts expect that the largest size will be the United States. The roles of data scientist and machine learning engineer are different despite some overlap, and it’s a great time for people interested in these career paths to learn more about them. In this blog, we’re telling you the differences between these two jobs so you can figure out which path suits you best.

What is a Data Scientist?

A data scientist uses data to help companies make good decisions. This process involves cleaning, collecting, and analyzing data to uncover patterns and trends. From there, businesses can look for problems and opportunities and make decisions based on data and statistics. Furthermore, companies use tools like artificial intelligence (AI) and machine learning (ML) to improve their analysis.

What They Do?

Data scientists work in numerous industries: healthcare, retail, manufacturing, etc. All industries can gain benefits from having data analysis. Here we will give you some common tasks that data scientists often do:

• Build statistical and machine learning (ML) models to find trends and patterns.
• Collect data from different sources and clean it to be consistent and accurate for processing.
• Use visualizations and reports to present findings clearly to stakeholders.
• Learn and apply new techniques, such as deep learning and reinforcement learning.

Skills They Need

• Programming: Python, R, SQL, Java.
• Data Modeling: Creating statistical and machine learning models.
• Visualization: Tools like Tableau to present findings effectively.
• Critical Thinking: Solving problems and making recommendations.

Education and Training

You need at least a bachelor’s degree in fields such as computer science, information technology, software engineering, etc. Many data scientists go on to earn a master’s degree as well. But a degree isn’t always a requirement, and boot camps are another option to learn the necessary data science skills over a much shorter time.

What is a Machine Learning Engineer?

A machine learning engineer builds systems such as algorithms, software applications, and predictive models that allow computers to analyze data, find patterns, and make predictions. Plus, they have to ensure that these programs are able to learn by themselves effectively after being trained to do so.

What They Do?

Like data analysts, machine learning engineers work in various industries: transportation, manufacturing, healthcare, etc. Their work is important because they develop ML technologies in these domains, which eventually help businesses tackle problems and make good choices. Here are the common tasks a machine learning engineer often does:

• Create machine learning models to solve specific problems.
• Debug and fine-tune machine learning programs to ensure accuracy.
• Work with software engineers, data scientists, and deep learning experts.
• Identify ways to improve existing machine learning technologies.

Skills They Need

• Proficient in languages such as Python, R, Java, and C++
• Know about neural networks and machine learning algorithms
• Knowledge of math concepts, including linear algebra and probability and statistics
• Knowledge of data modeling and cloud-based programs that support machine learning and artificial intelligence
• Communication and problem-solving

Education and Training

You need at least a bachelor’s degree in fields like computer science, data science, math, or statistics to work as a machine learning engineer. Plus, you can also pursue a master’s degree if you want to expand and deepen your knowledge. It doesn’t matter if you go to college to become a machine learning engineer since there are many boot camps and certifications that can give you all the important skills faster.

How Much Do Machine Learning Engineer and Data Scientist Earn?

This is the question we bet many often ask before working any jobs. No matter how much you love what you do, earning is crucial to keeping you passionate. According to Glassdoor.com, the average income of a machine learning engineer is between $133k and $213k a year, and the average income of a data scientist is between $128k and $208k a year. However, you need to keep in mind that the payment will vary based on your educational level, location, the industry you’re in, and especially how much experience you’ve had.

There you go; we’ve given all the important information for you to differentiate between a machine learning engineer and a data scientist. It’s up to you now to choose which path you want to take. Good luck!