Data Science is the field in which data is collected, analysed and interpreted in order to extract meaningful insights to solve business problems. The field of Data Science is extremely lucrative allowing business organisations to make efficient decisions. Accordingly, the need to evaluate meaningful data for businesses has invoked myriad job opportunities in Data Science. If you are a Data Science aspirant and want to know how to become a Data Scientist in 2023, this is your guide. The following blog post would naturally cover all the important aspects of becoming a Data Scientist including a step-by-step guide on the same.
What does a Data Scientist do?
In a business environment, a Data Scientist is involved to work with multiple teams laying out the foundation for analysing data. This implies that as a Data Scientist, you would engage in collecting, analysing and cleaning data gathered from multiple sources. The data would be further interpreted and evaluated to communicate the solutions to business problems. There are various other professionals involved in working with Data Scientists. This includes Data Engineers, Data Analysts, IT architects, software developers, etc.
Qualification and Eligibility
If you want to become a Data Scientist, you need to ensure that you have the proper skills and knowledge that makes you eligible for the position. Accordingly, you need to have a strong foundation in analytical and mathematical skills. You should be able to work with complex data sets to solve business problems. Furthermore, you should also have the skills to use software packages and programming languages like Python, R and SQL. You might become a Data Scientist by developing these skills through an accredited certification program.
Pre-requisites and Pre-experience
You might also be able to land your dream job if you possess some pre-requisite knowledge and skills or have prior experience in the field. These include:
- Strong mathematical and computer science background
- Experience in working with large amount of datasets
- Have the ability to work with Machine Learning and Statistical Modeling
- Strong skills of communication and visualization
- A willingness to learn by pursuing Data Science certificate programs.
How to become a Data Scientist-Step by Step
Now that you have understood what a Data Scientist does and the skills you require to become one, you must be eager to start your journey. But where do you start?
Below are some steps which you can follow as a path to becoming a Data Scientist. There are several factors which would enable you to become a Data Scientist. This has been laid out in multiple steps.
Earn a Data Science Degree or Certification
The first step in finding yourself to become a Data Scientist is undertaking a degree in Data Science. If you recently completed your higher education you would want to opt for a Bachelor’s Degree in Data Science which would help you learn from the basic fundamentals to advanced concepts. Further, If you’re already a graduate in a technical, you may opt for a Master’s Degree in Data Science.
On the other hand, Data Science certification courses online are also available opting for which may help you become an industry expert. Some of the best Data Science course online may include Wizard- the Data Science course for Working Professionals by Pickl.AI. They also have a Data Science job guarantee program which would ensure 100% placement in 5 months. Other Data Science course online is provided by Simplilearn, Upgrad, etc.
These courses would help you earn a certificate on Data Science where you would develop your technical skills and learn about basic and advanced concepts. By the end of the course, you would be an industry-ready Data Scientist.
Also Read: 9 tips to help you get a data science job
Learn Programming Languages
You need to be proficient in using programming languages if you want to become a Data Scientist. Programming languages include Python, R, SQL and SAS which you might be able to use for conducting mathematical tasks easily. One of the most popular programming languages is Python which is famous for its versatility and easy-to-use features. You can opt for Python for Data Science- a short-term course by Pickl.AI, to sharpen your skills and knowledge in the language.
Sharpen Your Skills
One of the most important steps in becoming a Data Scientist is to enhance and improvise your existing technical skills. These should include in terms of programming languages whereby you could learn Python and R at the advanced level. You should also develop your skills through data visualisation using Tableau, PowerBI and Excel. This would help you create charts and graphs and interpret data in a visual format. Developing your Machine Learning and Deep Learning skills would enable you to become efficient in predicting future datasets. Additionally, having soft skills like communication, teamwork and critical thinking abilities is also important. These skills would enable you to function in a workplace environment where you would need to indulge with different professionals to help make business decisions and solve problems.
Involvement in Industry-level Projects
One of the best ways to practice the skills that you developed is to involve in industry-relevant projects. These projects may involve using Machine Learning algorithms to solve business problems or may even include complex syntax. The projects are a way to demonstrate your ability in utilising your skills and knowledge in solving problems relevant to the industry. These projects should further be portrayed in GitHub whereby recruiters would be able to identify your proficiency in Data Science.
Get an Entry-Level Job or Internships
As you have been able to develop your skills and proficiency in Data Science, you would need to garner experience in the field as well. For a fresher who opts for a Data Science career, you may want to get an internship or an entry-level job in Data Science.
While you may opt for an entry-level Data Science job, you should apply for the position of Data Analyst, Business Analyst or Data Engineer. Further, being a fresher, you may also apply for internships where you team up with industry experts and gain knowledge on using Data Science tools.
Skills to Become a Data Scientist
In order to become a Data Scientist in a market where job opportunities are growing, you should have your skillset highly developed. These skills should include both soft skills and hard skills. Further, the soft and hard skills include:
Hard Skills:
- Python
- R
- Statistics
- Mathematics
- SQL
- Machine Learning
- Deep Learning
- Data Visualization
- Cloud Computing
- Big Data
Soft Skills
- Communication
- problem-Solving
- Critical Thinking
- Analytical
- Teamwork
- Business Acumen
Data Scientist Salary and Job Growth
The average salary for a Data Scientist in India is estimated to be Rs 8,60,316 annually. However, on average, those with less than one year of experience and freshers earn an annual salary of 5,71,493. On the other hand, those with an experience of 5 to 9 years of experience earn an average of Rs 14,20,229 per annum.
The opportunities in terms of Job growth for Data Scientists are high. By 2024, the market of Data Science would increase by 30% globally and would value $140.9 billion. Furthermore, the job roles for Data Science are would grow by 14% in India and would create 11 million jobs by 2026.
Parting Thoughts
From the above blog post, it can be concluded that to become a Data Scientist in 2023, you need to follow the above-mentioned steps. Having a degree or certification in Data Science would help you develop the required skills. Further, when you indulge yourself in industry-relevant projects, it helps in developing your profile. With the market of Data Science oozing job opportunities, developing your skills and earning a degree or certificate would be beneficial. You may indulge yourself in Pickl.AI’s Data Science course for professionals for developing your skills and knowledge. Additionally, the Data Science Job Guarantee Program by Pickl.AI ensures to offer you with 100% placement guarantee along with a 1 month internship opportunity with TransOrg Analytics.
