Data scientists and machine learning engineers build software and develop code, but for differing reasons. Compare the degree requirements, salaries, and outlook for these two professions.
Comparing Data Scientists to Machine Learning Engineers
The technological marvels of mass data collection and artificial intelligence are thanks to data scientists and machine learning engineers. While data scientists often work to make companies and other organizations more successful or to solve problems, machine learning engineers create programs that think for themselves.
Responsibilities of Data Scientists vs. Machine Learning Engineers
Data scientists and machine learning engineers both use large sets of data to make improvements in organizations or to make changes in the way a computer thinks. Data scientists are more involved in gathering, storing, and interpreting information. Machine learning engineers focus on making technological goods for consumers and companies. Though both learn how to write computer code, they develop different software using this computer language.
When a company or organization has an issue or question they need to solve by gathering data, they hire a data scientist. These professionals meet with the stakeholders and leaders of the study to learn the economic, efficiency, or customer goals. Using this information, data scientists develop computer programs using Java and other computer languages. Software providing complex algorithms is able to help these business-savvy techs find patterns in large sets of data. This data is then used to learn more about viewership, customer engagement, sales, workflow, and other issues.
Job responsibilities of a data scientist include:
Removing errors from data sets to avoid skewed results
Looking for only the pertinent numbers
Analyzing the data using statistical methods and writing a report the stakeholders can use to inform changes
Creating graphs, charts, and other visual displays of the data
Machine Learning Engineers
Machine learning engineers develop programs that control robots and computers. Extensive research on machine learning applications and the ways these can innovate production and other industries allows these professionals to understand how machines can benefit our world. The algorithms they create allow a machine to find patterns in its own programming data, teaching it to understand commands and even think for itself. The artificial intelligences seen in automatic vacuums and self-driving cars are the 'thought children' of these engineers.
Job responsibilities of a machine learning engineer include:
Researching new technologies and implementing them in machine learning programs
Finding the best design and hardware to use when building the robot or computer
Developing tangible prototypes to show stakeholders
Putting the machines through various tests to ensure they function as planned
If you think a career as a data scientist sounds exciting, you could also seek information about a job as a computer information systems manager, because both apply technology to a business plan. Similarly, if you're interested in a position as a machine learning engineer, you could look into a job as a product engineer, since both develop goods we use daily.
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