How to Build a Career in Data Science?

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With data being considered the new oil, data science has become everything in the business environment. With the right set of advanced tools and frameworks, data science yields insights that lead to better decisions and offer an edge over competitors. This is the very reason companies, regardless of their size, are now adopting data science for fear of missing out, making data analytics expertise one of the most in-demand skills of the present job market. This is good news for professionals and fresh graduates who are skilled in data science. In fact, online training providers are now offering data science courses to make professionals ready for jobs in this field. 

There is no shortage of areas where data science can be applied. Companies across the world have realized the importance of data science, whether they belong to IT, supply chain, marketing, research and development, healthcare, banking and finance, or even other business verticals. Companies like Amazon, SAS, IBM, Google, Facebook, Oracle, and PwC are the top companies that hire data scientists in large numbers. Those professionals who love diving deep into data and bringing out hidden trends and correlations can best fit for a job in this field. 

One may now wonder ‘How to actually start a career in data science?’ well, you can check out the details we have mentioned in this article and get an answer to this question.

Starting a Career in Data Science 

Let us first talk about the educational background required for a data science career. You may have a lot of questions regarding which degree is needed, and whether or not a technical background is compulsory. Well, a graduation degree in computer science, information technology, electronics, or any related field is recommended to get started with data science. Many surveys have found that existing data scientists hold a master’s degree or a Ph.D. While these qualifications carry a lot of weight, the institution that issued the degree is not important. Professionals from unranked universities have also joined this field and succeeded in building a data science career. 

In fact, a technical background is recommended but even if you don’t have it, you can carve out a career path in this field. Obviously, it would require more hard work on your part. A study by 365 Data Science revealed that 25% of respondents of the overall data scientist resumes surveyed were from unranked universities and around 40% of them reported having taken an online course. This is specifically beneficial as professionals need not go back to university for another few years to do a specialization in data science. Whatever degree you hold currently, you can enroll in a relevant online course. 

Let us now focus on the skills required to become a successful data scientist. First off, you need to become well versed in core math concepts like probability, linear algebra, calculus, and have a sound understanding of statistics. Next, you should polish your programming skills, some of the popular ones include Python, R, Java, Scala, and C++. Note that you don’t have to gain expertise in all the languages, any one is enough, preferably Python or R as they are dominant ones. Now you are ready to dive into the phases of the data science lifecycle that majorly include data acquisition, data cleaning, data modeling, data analysis, and data visualization.  

Next, data scientists need to work a lot with databases. So, knowledge of database management systems, Structured Query Language or SQL (language used to work with data in database) MySQL, MongoDB, Oracle Database, and Microsoft SQL Server among others is essential. Additionally, it is important to explore the concepts of machine learning. It is widely used in data analysis and identifying patterns from large datasets so as to gain valuable insights. Finally, you need to have a clear understanding of big data technologies like Apache Spark, Hadoop, and Apache Kafka. This is because present-day data is massive and cannot be processed through traditional tools and techniques. 

The Next Steps

Now that you have understood what skills lead to a data science job role, you need to decide whether you want to do self-study or take up an online training course. If you are a beginner or someone from a non-technical background, then an online course is highly recommended for you. The highly qualified instructors will teach you everything from scratch and you will not have to worry about anything. Topics like using MS Excel, R, or Python for data analysis, creating data models, implementing machine learning models, applying data science to various real-world scenarios, statistical analysis would be thoroughly covered in such training courses

Eventually, when you are ready, start looking for entry-level jobs in data science. Since you will not have any experience to show, you can demonstrate your practical skills by working on industry projects. You can also participate in various online competitions where you would need to use data science concepts to solve real-life challenges. Another option is to go for an internship instead of a full-time job. By working as an intern, you will gain the required skills and experience and then convince the employers of your credibility working as a data scientist.   

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Michael Cainehttps://amirarticles.com/
Michael Caine is the Owner of Amir Articles and also the founder of ANO Digital (Most Powerful Online Content Creator Company), from the USA, studied MBA in 2012, love to play games and write content in different categories.

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