What Does A Data Scientist Do?-A Detailed Explanation

          What is the similarity between the headlines you see on your News app, Google search rankings, your Netflix homepage, and your Spotify playlist? Think about it ... take a minute.

Any guesses?

Well, it's data science! Data science determines which headlines matter most to you. It also determines which search results are most relevant to your search query, what show you watch next, or what kind of music you like. ?

And yes, while data science is a field that originally found its use in technology, it will now transform multiple sectors, from retail, telecommunications and agriculture to healthcare, transportation and more. science "is widely used today, but few really understand what it means.

What exactly does a data scientist do? In today's blog we talk about data science, data scientist jobs, data scientist careers, data scientist salary in India and more ...

          Well, let's first clear up a common misconception: data science is not a linear field, there are many forms, as in engineering, there are electricity, mechanics, construction, just like in data science, there are numerous verticals.

For example, data scientist Robert Chang says he focused on growth hacking using data on Twitter, but now on Airbnb on machine learning models that use similar data.

In principle, data can be used differently, not only depending on the industry but also depending on the company and its goals. This means that the science behind this data can also be manipulated and adapted depending on usage.

Let us now come back to our initial question, what exactly do data scientists do?

          Data Scientists build a strong database to analyze and solve problems. Then they process and clean up the data and only keep what is relevant to your project. Then they do an initial exploration of the data and examine what is there. Record, the longer the exploration process can take. They then apply data science techniques such as machine learning and statistical modelling to measure the results. You visualize the data or present it to key stakeholders in an easy-to-understand way, and eventually repeat this process for each new problem, hypothesis, or business opportunity.

Well, the world now definitely knows that data science works, at least in tech, but it has applications in other industries. From cancer research to autonomous cars to more efficient logistics, data scientists are on the move in various places.

This means that there are numerous possibilities for data scientists to use their know-how.

          This also means that the data scientists to have a breakthrough in their careers are learning a variety of skills such as mining, cleaning and data organization, learning new technologies as they go, analysis and insights also related to a new adjustment. Data tools, and more.

          Jonathan Nolis, a professional who previously worked at GitHub and LinkedIn, divides the role of a data scientist into three components:

Although many working data scientists are currently "generalists" and do all three. We are seeing distinct career paths and more and more specializations emerging within the field. For example, data engineers clean, aggregate, and organize data from disparate sources and transfer it to data warehouses. But Business intelligence specialists Identify trends in data sets. Meanwhile, Data architects design, create and manage an organization's data architecture. So if one chooses a "generalist route" or opts for a specialization depends on the person's strengths and interests.

          By many accounts, becoming a data scientist is a highly desirable career. For five years in a row, based on median base salary, the number of active job openings, Glassdoor ranked data scientists as one of the ten best jobs in America. It may even sound funny, but the Harvard Business Review called data science "the sexiest job of the 21st century".

Google's Chief Economist, Hal Varian, told McKinsey- "the ability to take data to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it, that's going to be a hugely important skill in the next decades."

          So if data science seems like a field that interests you and you want to learn more; you can check tonnes of blogs on the subject on the InsideAIML's website. They will guide you through the nuances of the field in detail. And of course, if you have any queries, doubts or questions, you can comment below, and we'll do our best to get back to you!

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