Advance Your Machine Learning Engineer Career

You'll want to make sure you have a strong foundation of machine learning fundamentals before moving onto advanced concepts and classes. It's helpful to know the fundamentals of scalable data science and mathematics, including linear algebra and multivariate calculus. Programming, especially in Python, is also recommended, as is basic knowledge of SQL. ‎

With your master’s degree in data science, you can explore many data science jobs or continue your educational pursuits by applying for a PhD in data science. The roles below illustrate some of the jobs you can pursue once you’ve earned your master’s degree in data science, includng machine learning engineer:

• Senior data scientist: Working as a data scientist typically requires a bachelor’s degree, but you may qualify for more senior-level roles with a master’s. Data scientists typically design algorithms to collect and interpret data.
• Data engineer: A data engineer designs and builds systems to handle a lot of data so that data scientists and data analysts can work with it.
• Data architect: A data architect drafts frameworks businesses can use to handle data, often with the goal of making sure it meets any compliance requirements.
• Machine learning engineer: Machine learning engineers often sit on data science teams. They design, build, and maintain machine learning algorithms and systems.
• Statistician: Statisticians can work for public or private organizations and often look for trends in data by collecting and interpreting it.
• SQL developer: This role sits in between software development and database engineering. SQL developers often work to create on maintain SQL-specific databases.

Read more: Is a Master’s Degree in Data Science Worth It?‎

Machine learning skills can open the door to a wide range of careers, as more and more companies seek to harness these techniques and artificial intelligence (AI) to automate a growing range of processes. Some companies may specifically hire for machine learning engineers, but machine learning skills can also be important for data scientists, data analysts, and data engineers.

There are more specialized roles available for machine learning experts, too. Many companies in the financial industry may employ business intelligence analysts and decision scientists who can leverage machine learning skills to automate systems for delivering market insights. And companies building Internet of Things (IoT) that rely on voice recognition or other human inputs may employ natural language processing engineers or human-centered machine learning designers.‎