Q&A

Is it harder to become a software engineer or data scientist?

Is it harder to become a software engineer or data scientist?

Software engineering is neither tougher nor easier than data science. Both domains demand a different skillset for operating. Whereas, a data scientist requires a commanding knowledge in Math, data collection, and analysis for a better understanding of their job.

Why do data scientists make so much money?

To an economist, this is a simple case of demand and supply, but this is arguably one of the prime reasons why data science pays so well. Companies today are in search of qualified candidates who can help them better understand big data, but these qualified candidates are scarce.

Can a Python developer become a data scientist?

It’s possible to work as a data scientist using either Python or R. Each language has its strengths and weaknesses, and both are widely-used in the industry. Python is more popular overall, but R dominates in some industries (particularly in academia and research).

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Is data science the highest paid job in America?

Sure, it might be more fun to be a painter, teacher or police officer. But if you’re looking for the highest paid profession, data science is hard to beat. Yes, CEOs make more, coming in at a median salary of $740,589. But among the jobs available to the remaining 99.999\% of us, data-scientist salaries are hard to beat.

Where do software engineers make the most money?

San Francisco pays software engineers the most; Detroit, the least. For software engineers, geography has a tremendous effect on their paychecks. In the San Francisco Bay Area, software engineers make a median salary of $142,000 – in Detroit, they make $88,0000. Of course, the cost-of-living varies greatly across these regions as well.

Why are data scientists unhappy in their roles?

The company then get frustrated because they don’t see value being driven quickly enough and all of this leads to the data scientist being unhappy in their role. Robert Chang gave a very insightful quote in his blog post giving advice to junior data scientists:

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How many hours a week do data scientists spend looking for jobs?

But the truth is that data scientists typically “spend 1–2 hours a week looking for a new job” as stated in this article by the Financial Times. Furthermore, the article also states that “Machine learning specialists topped its list of developers who said they were looking for a new job, at 14.3 per cent.