Career Development

Machine Learning Engineer vs Data Scientist, what are the differences?

Definition: What is Machine Learning?

Before explaining the differences between these two jobs, it is interesting to present a definition of Machine Learning or ML:

Machine learning (ML) is a branch of artificial intelligence that allows computers to learn from data and improve without being explicitly programmed for each task. It uses algorithms to analyze data sets, identify patterns and make predictions or decisions based on this information.

The differences between ML Engineer and Data Scientist

The professions of ML Engineer and Data Scientist are two very similar roles:

  • These are generally positions ofengineers specializing in Data, with skills in Data Science and Machine Learning
  • They both work on Machine Learning and AI models
  • They have similar skills in the following technologies and languages: Programming in Python, Pandas, Pytorch, Tensorflow

In small companies or startups, these positions tend to merge into a single profession that covers all spectrums. The more a company and a Tech/Data team develops, the more the distinction between these jobs may appear:

Here are the specificities of each of these two professions, as generally understood in the job market:

  • THE Data Scientist aims to identify use cases and respond to them through machine learning model development. In certain aspects, the role of Data Scientist has a stronger R&D dimension than the job of ML Engineer.
  • THE Machine Learning Engineer aims to enable models of ML to scale. Its objective is to train models on a large volume of data, to put them and maintain them in production. In certain aspects, his missions can approach the role of Data Engineer.

👉 Find our job description on the position of Data Engineer to understand the missions of this role

Here is a diagram that summarizes the similarities and differences between Data Science and Machine Learning

Differences between Data Science and Machine Learning
Diagram of the differences and similarities between Data Science and Machine Learning

Source : https://www.coursera.org/articles/data-science-vs-machine-learning

Presentation of the Data Scientist position

The Data Scientist analyzes and interprets complex data to help make data-driven decisions, using statistics, machine learning and analytics techniques to extract insights and predict trends.

👉 Find our job description on the position of Data Scientist to find more details about this role

Presentation of the Machine Learning Engineer position

The Machine Learning Engineer designs, builds and deploys machine learning models in production systems, optimizing their performance and ensuring their integration with existing technologies.

What salary for a Data Scientist or Machine Learning Engineer?

The salaries of Data Scientists and ML Engineers are significantly close, depending on the number of years of experience.

  • At the start of your career, expect a salary between €38 and €45k for a beginner engineer. These salaries can go up to €50,000 for engineers graduated from the most prestigious schools.
  • For a level of experience included between 2 and 5 years oldsalaries are generally between 50 and 70 k€
  • For more experienced profiles, with Lead and Managementit is necessary to count a range between 80 and 100 k€
  • For a position of Head of Data Sciencesalaries are included between €100k and €200k

Career developments for a Data Scientist or ML Engineer

For a Data Scientist or one Machine Learning Engineercareer developments may include:

  • Specialization in specific areas of machine learning, data analytics or artificial intelligence, such as deep learning, natural language processing (NLP), or predictive analytics.
  • Technical leadershipby becoming a recognized expert in a technical field, guiding projects and innovations.
  • Project management Or leadersupervising teams of data scientists or ML engineers, and managing projects from end to end.
  • Product managementusing technical knowledge to guide the development of data- or AI-driven products.

How to become an ML Engineer or Data Scientist?

The classic route is to follow training within an Engineering School, with a specialization in Data, Data Science or Statistics. This is the school curriculum

Other training courses exist at university, with specialized masters in Data Science.

Finally, some retraining training exists. However, it can be difficult to directly find a job as a Data Scientist after a bootcamp or retraining.

How to recruit an ML Engineer and a Data Scientist?

Are you a company looking to recruit? The possibilities available to you:

To go further on the Big Data and AI professions

Find our article on professions and differences between Data Analyst, Data Scientist and ML Engineer

Find our article on the AI ​​professions that will be recruiting this year: Artificial Intelligence Jobs

Looking for job offers for Data Science and ML positions? Find all Data Scientist job offers on the Licorne Society recruitment platform.

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