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Machine Learning Engineer vs. Data Scientist

ML engineer vs Data scientists

As every organization is moving towards building the most advanced enterprise-ready solutions, a demand for hiring Machine learning engineers and Data scientists is increasing a lot. I have observed that the majority of the people have no clear understanding between both and ultimately think that both do the same work. Then ultimately they end up with building ineffective business models. Thus hire Machine learning developer or Data scientist you need to understand the thin line between both.  We are here to help you understand Machine learning Engineer vs data scientist and improve your understanding.

Don’t worry ! stay tuned to identify the thin line between both and pick a right expert for your business.

Who is a Machine Learning Engineer?

Machine learning engineers are responsible to take the business solutions prepared by the data scientists and forward them to production.” They are well versed in building buildings that control computers and robots.

Who is a Data scientist?

While a data science developer is to build a model with the help of machine learning or deep learning to solve various business problems. They usually explore various business aspects with the help of programming languages such as java.

So, What’s the difference ?

Machine Learning Engineer vs. Data Scientist – The Skillset

Machine Learning Engineers need to have a deep knowledge and core expertise in advanced linear algebra, statistics, data structures, NLP, and other aspects to build a software.Also They are expected to be focused on the technical and more into programming part.

Data scientists are considered as more research-oriented because they require comprehensive theoretical and practical understanding in algorithm development as well as expertise in a variety of machine learning techniques, sometimes even deep learning.

Machine Learning Engineer Salary vs Data Scientist Salary

As per the Payscale data, ML developers make on average a range of $93 to $149k yearly while Data scientists make between $85K and $134K annually in pay.

Here it is needed to keep in mind that Data scientist is considered a more broader role than Machine learning. Also based on the demand we can expect a change in the average salary range of both.

Machine Learning Engineer vs. Data Scientist – Roles and Responsibilities

The role of an ML engineer is to run data to make sure to come up with a smooth operation and production process while building a software architecture. Also by keeping statistical models in mind they are required to build and maintain a scalable ML model in production.

Data scientists are just like an architect who needs to do a lot of experiments and study while coding to explore various data structures and insights to build a predictive model. Also to verify the model quality Data science developer is also required to do A/B testing.

Wrapping Up:

Thus we can say that the demand of Machine learning engineers is very near to the demand of data scientists only. As with time businesses would require more advanced business models and for the clarity of Machine learning engineer vs Data scientist needs to be there.

Now it is time for you to decide whom to hire between both and join hands towards a more advanced and bright business future !!!

Hope you liked it !

 

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