Recruiting for hundreds of roles in Data, Analytics and Machine Learning has given us a good grasp on salary benchmarks in Amsterdam. Now, drawing on years worth of our own data we’ve crunched the numbers to present Orange Quarter’s Data and Analytics Salary Review for Amsterdam.
Data Science. Big Data. Machine Learning. Artificial Intelligence. These are all powerful pairs of words. Let’s see with real studies, numbers, and images why you should consider learning about any of them.
Why learn Data Science or Machine Learning?
Data Science has been defined as ‘The Sexiest Job of the 21st Century’ by Harvard Business Review. Glassdoor, a world-known website for job seeking, ranked Data Science as the best job in America for 2019. Bloomberg regards Data Scientists as the new Superheroes.
Whether it’s the media, articles, job postings or interviews of top leaders from companies such as Google and Facebook, everyone seems to have been talking about Data Science and Artificial Intelligence. If you’re like most, you would also be thinking — How to become a Data Scientist?
What is the scope of work and the role of the data scientist.
We are increasingly hearing about this “new” craft called Data Science and its professional, the Data Scientist. But in the end, what does a Data Scientist do? Will the individual really work in a white coat and goggles? To analyze this, we may first understand that it is science, what has changed in the last decade to legitimize this new concept and how this new area and profession compare with the rest of the new and old functions?
If you poke around in the early history of the term data science, you see two themes coming together. Allow me to paraphrase for your amusement:
Big(ger) data means more tinkering with computers.
Statisticians can’t code their way out of a paper bag.
And thus, data science is born. The way I first heard the job defined is “A data scientist is a statistician who can code.” I’ll be full of opinions on that in a moment, but first, why don’t we examine data science itself?
Data Science is such a broad field that includes several subdivisions like data preparation and exploration; data representation and transformation; data visualization and presentation; predictive analytics; machine learning, etc. For beginners, it’s only natural to raise the following question: What skills do I need to become a data scientist?
Modern data science emerged in tech, from optimizing Google search rankings and LinkedIn recommendations to influencing the headlines Buzzfeed editors run. But it’s poised to transform all sectors, from retail, telecommunications, and agriculture to health, trucking, and the penal system. Yet the terms “data science” and “data scientist” aren’t always easily understood, and are used to describe a wide range of data-related work.
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