What is career growth in data science?

Data Science, AI and ML
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#1
As close to 70% of data science projects & implementations are centered around data; the career of a typical data science aspirant invariably starts from data engineering wherein he/she learns to clean, massage and harmonize data to make it in a format on which statistical analysis can be done. The next stage in career growth phase is implementing statistical models and mathematical algorithms on the harmonized data to derive useful and relevant insights from the business.
Post spending a considerable amount of time in previous roles, a data scientist invariably moves to a more front-end role wherein he/she delivers insights,

inferences & prescriptions to business.
Furthermore, data science is an extremely dynamic field and could be different basis the organization that an individual work for. The career growth may be organic in large organization while it could be extremely fast in small & medium scale enterprises.

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#2

Data Science has a wide career scope in the 21st century as every application we use today relies on data. Most of the companies (90% of them) rely on data for extracting crucial information that helps their business to grow. For this, organizations hire Data Analyst and Data Scientist for performing the task of analyzing and interpreting data. So, Data Science will exist there for a long time and there is a huge scope of growth in Data Science as well as various fields related to Data Science such as Machine Learning, Artificial Intelligence, and Deep Learning.

There are plenty of job opportunities in Data Science with good pay that makes it a promising career. According to Forbes, the Data Scientist job is listed among the top 10 job profiles in the IT industry. Also, the average salary of a Data Scientist in the USA is $125,500.

As we are moving towards a well-organized digital era of automation companies would be requiring Data scientists. So, you must be ready for the upcoming opportunities in Data Science by upskilling yourself.

#3

The majority of businesses use data analysis to aid in their expansion. Data scientists are in high demand in the technology industry, as well as other large businesses like FMCG, logistics, and others.
Some of the lucrative Data Science occupations for candidates include:

• Data Scientist

A Data Scientist looks into different data trends to see how they affect a company’s bottom line. The capacity of a Data Scientist to explain the relevance of data in a way that everyone understands is crucial.

• Data Analyst

The duty of a Data Analyst is to examine data in order to detect industry trends. He contributes to the creation of a straightforward view of the company’s operations.

• Computer Engineers

Computer engineers are sometimes referred to as the company’s backbone because they work for the organization’s heart. They are responsible of developing, building, and maintaining a large database. They are also responsible of creating data pipelines, ensuring proper data flow, and ensuring that data reaches the appropriate departments.

• Analyst for Business Intelligence

A market intelligence consultant aids in the analysis of obtained data in order to boost a company’s efficiency and profits. Their work is more scientific than theoretical, and it demands a deeper knowledge of ordinary devices.