Data Visualization in R

It’s no surprise that today’s economy is moving toward data analytics and data-driven technologies. Big corporations, multimillionaire conglomerates, and even governments have spent a lot of time and resources collecting large amounts of data. Various organizations from all verticals are looking for data science specialists to help mine insights from extensive data.

There is a massive demand for data scientists in the analytics sector, but some confusion among young aspirants regarding the said profession exists. In this guide, you’ll learn about the particularities of a Data Scientist Career Path, including the prerequisites, required skills, and career prospects.

Who is a Data Scientist?

A data scientist can be someone employed to examine, analyze, and decode digital data to help a business in its decision-making procedures, product marketing, understanding consumer behavior, etc. The work involves understanding statistics, computer science, and some knowledge about current business trends. A data scientist’s roles and responsibilities majorly include analyzing the data, forming insights and helping management take required decisions.

As different industries and sectors are now incorporating data science, the path to becoming a data scientist is the same, but some employers may expect additional skills.

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Why pursue a career in Data Science?

As every form of business is eventually shifting toward tech-based systems, small and large business owners are looking for individuals who are experts in deconstructing and interpreting data. Listed below are some essential factors highlighting why you should decide to pursue a career in data science:

Great salaries
Remarkable chances of professional growth
Currently high in demand
A variety of career opportunities
Work that is continuously challenging
High stature career
Exceptional prospects

Data science can alter our industries as well as our society. Due to increased market demand and a shortage of professionals working in this field, it promises a profitable career.

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Is Data Science the right career path for you?

The Data Science Career Path might sound attractive to some as you don’t need a specific degree to start practicing as a data scientist as other conventional jobs demand. An aspiring candidate needs the right skills and an interest in working with digital data. It’s crucial to find an answer to this question before making any fixed decisions.

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Becoming a Data Scientist is not easy as it demands the ability to continuously learn about new concepts belonging to various fields, which may or may not interest an individual. The following section mentions the skills required to become a data scientist.

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Skills needed to become a Data Scientist

From Apple to Ola, each tech company wants to take the lead in data science, and it is now clear that data science is one of the rapidly growing fields.

The path to becoming a Data Scientist is not very complex, but there is a list of required skills. Developing some of these skills might take time, but as long as you’re dedicated, you can become a successful data scientist.

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Learn the fundamental concepts of data science: you must understand the basics required in this field, such as statistics, machine learning, text analytics, etc.
Statistics - Statistics are essential in this field because machine learning algorithms function on mathematics and stats. Hence, it would help if you had a general understanding of math and statistics.
Learn critical programming languages - To transform your analysis into action via a computer, you need to know different programming languages. To learn a programming language, you must have an exceptional love for computers. You can start by mastering Python, the most common programming language.
Data analysis - having an experimental and curious mindset will help you search for different ways to handle digital data and extract the most meaning out of it. For this, you can start with SQL, a standard language for storing and manipulating data in databases.
Data visualization - to become an expert in data science, you must create great graphs and charts representing your data. Such graphic representation helps to convey your findings quickly. Several tools are available in the market, such as Tableau and PowerBI.

What are the Different Career Paths for Data Scientists?

The Data Scientist Career Path is exciting but time-consuming as it requires you to boast a vast skill set. These career roles can be pretty confusing to some. But the positive part is that it allows you to explore a variety of career roles. In specific industries, you might not find a lucid distinction between these roles but listed below are different yet somewhat related career prospects that can be explored.

However, as the job sector is continuously changing, data scientists will have a clearer idea of what career paths to follow depending on their skillset.

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1. Data Scientist

A Data Scientist is considered a notable role in any organization. This is why this role is most looked out for by professionals nowadays. Many companies use this role in their job listings as it is easier for interested candidates to search for and apply. Other alternate designations that companies might use include ‘market analyst’ or ‘business intelligence exert.

2. Data Analyst

Companies use this job title to convey that it includes more technical knowledge. Alternate terms include ‘analytics professional’ or ‘market analyst.’ The role of a data analyst involves using the organization’s data to bring usable insights that can help a business. The projects that data analysts work on keep changing; for example, a data analyst might start working with the marketing team and then later shift to production.

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3. Data Engineer

A data engineer is the biggest strength of any company. Organizations are mainly looking for data engineers to help with software development. A data engineer must work on the company’s core database; it demands exceptional knowledge of programming languages and coding skills.

4. Business Analyst

Business analysts share a role quite similar to that of data analysts, the significant difference being how they function. As the name suggests, business analysts are considered skilled in business-related fields and the process involved. They usually assist data analysts by offering new business views, domain knowledge, etc.

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5. Clinical Data Manager

Clinical data managers must collect data from medical research, surveys, clinical trials, pharmaceutical projects, etc. They make sure the gathered data is organized and reported without errors. This role is specifically relevant to the healthcare industry.

6. Marketing Analyst

Marketing analysts work with a fixed function of business; marketing. Marketing is considered an essential part of any business. How a company markets its products affects its sales and services, affecting the overall industry. Marketing analysts study consumer behavior and help create functional methods for conducting marketing campaigns within a determined budget.

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Conclusion

Becoming a Data Scientist is not easy, but it is a rewarding career choice that offers excellent career prospects which are lucrative. Follow this guide to identify if Data Science is the right career path for you, and remember, making this choice is just the beginning of your journey. And to make your journey easy, you can always opt for our Data Science Course in collaboration with IBM which offers a 100% job guarantee. You get to learn from working professionals and industry experts who have decades of experience with hands-on industry projects and assignments. Enrol today and give a kick-start to your data science career.

Frequently Asked Questions

1. Is Data Science a lucrative career option?

The field of data science is rapidly growing, and there is a massive demand for data scientists in different areas. Hence, it is a great career path, and the salaries are exceptional due to high demands.

2. How do I begin forming a career as a Data Scientist?

The first part is to know in detail what all skills this field requires, followed by honest self-evaluation. The next part involves learning the skills needed to become a data scientist.

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3. Does Data Science demand an excellent knowledge of Math and Statistics?

Yes, indeed. Working with numbers and extensive calculations is the core of a data science career. You don’t need to hold a higher degree in math or statistics, but elementary knowledge is necessary.

4. Does Data Science ensure several career prospects?

Yes, a data scientist can work in different organizations and occupy different roles such as market analyst, clinical research analyst, business analyst, etc.

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