Data scientist is one of the most in demand careers of the 21st century. Every organization from private to government to non-profit, there is a lot of data that has to be sorted, analysed and applied for a vast range of purposes. 

But it is not easy as it sounds. It can be challenging to find the right answers and sort through data to make right strategic decisions. How can organizations create engaging activities or marketing plans to boost potential operations?

This is the job of a data scientist. They are skilled and experienced to gather, organize and analyze data for helping businesses across various verticals. Data scientists may come from different technical backgrounds. Data science degrees include majors in computers-related subjects, maths and statistics. They are also trained in human behaviour/business to deliver more precise results at work. 

Therefore, for data scientists an infinite amount of data and work are available in the market. In this article, you will get to know what they are, what they do, what skills do they need and who they serve.

What is a Data Scientist?

The primary role of a data scientist is to gather, analyze and sort information to get to a result. It can be done via various techniques such as Data Visualization. The data is presented in virtual form which permits the users to search for patterns that will not be visible if the data is presented in the form of spreadsheets.

Creating advanced algorithms to evaluate numbers and sorting jumbled data to something useful is also part of becoming a data scientist.

Let’s understand this with an example-

A smartphone company wants to know who among their existing customers are likely to switch to their competitors. They can use services of a data scientist to take a look at millions of data points to reach a conclusion. They may find that customers within a specific age limit or using certain applications are most likely to change their preferences. 

Based on this analysis, they can change their marketing or business plans to retain their existing customers. Netflix is also a great example of using data management in real-time. Their video streaming program is designed in such a way that it will give video suggestions based on previous viewing history. 

Who is a Good Candidate?

Can you become a good Data Scientist? What are the key skills to become a data scientist? What are the unique characteristics that apply to the data scientist?

One of the most crucial things you need to become a data scientist is a curious nature with constant urge to learn more. There are always millions of data points to be analysed and interpreted, a Data Scientist should always be curious to find the right possible answers. 

You should also possess a strong ability to organize. The information is to be sorted in such a way that clear patterns are visible to make right decisions for the businesses. Stubbornness to look for answers even if you have to reorganize or re analyze data points a zillion times in the hopes that a new viewpoint will lead to a “Eureka!” moment.

Other characteristics that help you become a data scientist are staying focused and attention to detail. 

How to Become a Data Scientist?

Here are the 3 steps to becoming a data scientist: -

  1. Bachelor’s degree in IT, computer science, maths or other related subjects.
  2. Master;s degree in data or other related subjects.
  3. Relevant experience in the industry you want to make your career in. 

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Data Scientist Education Requirements

You cannot be a data scientist without a proper educational background. You need to have at least a bachelor’s degree in IT IT, computer science, maths or other related subjects. Around 73% of the professionals in the data science field are graduate while 38% hold a doctorate degree. If you want to reach leadership positions, then you must have a master’s or PhD degree.

Many institutes also offer graduate degrees in data science. It gives professionals the required skills to process and analyze a complex set of data to make right technical or marketing decisions.

Here are some of the other degrees that can get you started with your data science career:

  • Computer science
  • Statistics Physics
  • Social science
  • Mathematics
  • Applied math  
  • Economics

After you graduate with flying colours, you can opt for internships or training in your desired industry and enhance your skills. You will develop skills such as coding, analysing large amounts of data, problem solving, etc.

Must Read: What is Data Analytics?

Data Science Specializations

Data Science is required by every business around the world. Hence, you can choose from a wide range of specialization options to build your career in. Data scientist can choose specializations from specific sections of industries (insurance, finance, automotive, healthcare, defence) or business-related fields (marketing, technical, pricing). 

Let’s understand this with an example: -

A data scientist can work for car dealers to create effective marketing strategies by analysing their existing customer database and patterns. He or she may also help in determining right offers and set competitive pricing for their products and services. 

They can also work in the defence department and specialize in analysing the threat levels and creating right strategies. For start ups, a data scientist can find the right data points to grow and sustain their business. 

For insurance, they can analyse customer spends, income and type to create specific offers for a specific set of customers. 

Data Scientist Jobs

There are no specific work settings for a data scientist especially in today’s scenario. They can work from their homes, office or on site but ensure effective communications with their teams. Their majority of time will be utilized in uploading numbers and data into the system, doing thorough research, writing codes, quantitative analysis, etc. 

Usually data scientists have to work in a fast-paced work environment but some company may prefer them to work in a slow and predefined process. It all depends on your specialization and the nature of business you are working for. 

What are the drawbacks of becoming a Data Scientist?

Every field has its own set of pros and cons. The advantages of becoming a data scientist has already been covered in detail in this article. Let’s discuss its drawbacks. Data science is a very challenging field which always keeps you on your toes. 

You have to be constantly evolving and upgrade your skills time to time. It may happen the software you have built your expertise on may become completely obsolete after some time or may not be applicable in other companies. Therefore, you have to suddenly start from scratch and learn a whole new system. It can be very consuming and troubling sometimes. Therefore, if you are passionate about data and learning new skills, then you can definitely go for this. 

Salary of a data scientist

The job of a data scientist is not easy, therefore they are paid really well and can enjoy a secure financial future. On an average a data scientist with upto 5 years of experience may earn anywhere between $80,000 to $110,000 per year. 

A salary of around $150,000 can be expected after 8-9 years of experience and $232,000 can be expected after 10-12 years of experience. 

The demand for the data scientists is at an all time high. They are 50% higher in demand as compared to other professionals in similar fields such as software engineers and data analysts. The number of data scientists has grown more than 200% in the past 5 years.

Summing up

In the upcoming years, the majority of businesses will rely on data scientists to make right strategic decisions. The big data analytics market is set to reach $103 billion by 2023. They will need someone or a team to organize, store and interpret their data. 

Also Read: Data Scientist Salary Reports From Around the World

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Armin Vans
Gyanesh Mishra have delivering quality training on Microsoft Dynamics ERP Product, Data Bricks, Azure Data Factory, Azure Stream Analytics, Cosmos DB, Azure SQL Database, Azure Synapse Analytics, Azure Storage Account, Azure Data Lake Store, and SQL Server BI products.

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