If you strive to become a data scientist, there’s some great news for you: data science is one of the most trending career options available in the twenty-first century. In addition, surveys reveal that data scientists are in higher demand as compared to candidates belonging to other industries. Since this is just the beginning of this niche, jobs in data science are here to stay.

However, conducting research about this emerging career option on Google may disappoint you. That’s because there are so many resources, career paths, and advice suggested by different people that you may get confused as to which career path to choose. But you don’t have to learn data science skills all at once. Instead, it’s better to explore job descriptions of data science fields closely. This will help you identify which jobs suit your current skills the most, and which ones require you to learn some extra data science skills.

Below are some of the most common data science jobs and their descriptions to help you choose the right career path:

Data Analyst

As a data analyst, you’ll be required to pull data from MySQL databases, workout Excel pivot tables, and product bar charts, line charts, and other such data visualizations. Occasionally, you’ll be analyzing A/B test results too. Though these are routine tasks, working as a data analyst will help you get equipped with these basic skills.

Analytical Skills Required

Education – 88% of data scientists have a Master’s degree while 46% of them have PhDs. So you need to possess an exceptionally strong educational background so that you can develop in-depth knowledge that’s highly crucial to start working as a professional in this field. To start off, choose among Mathematics, Statistics, Computer Science, or Engineering as your preferred field of study.

R – Though there are numerous programming languages you can learn to achieve a competitive edge in data science, R is the most preferred choice for beginners. That’s because it’s not only the most popular language among data science professionals, mastering the core areas such as data manipulation, machine learning, and data visualization can be much easier as compared to learning the same skills set in other programming languages.

Computer Science Skills Required

Besides having a strong grip on R, being competitive requires you to learn the following technical skills:

  • Python coding – other than Java, C/C++, or Perl, this is the coding language that’s highly preferred in data scientist job requirements.
  • Hadoop platform – Though this isn’t a common requirement, having strong expertise in Hadoop platform can be heavily preferred in numerous organizations.
  • SQL Coding/Database – NoSQL covers a larger part of data science. However, employers can still expect you to use SQL for writing complex queries.
  • Unstructured Data – Whether it’s from video feeds or social media, data scientists should be able to use unstructured data while delivering specific tasks.

Data Engineer

This job is a good fit for companies that have a huge amount of data to be analyzed. As a data engineer, you’ll be required to set up data infrastructure for the company. This organized data will be utilized by high-authority personnel to devise strategies in terms of moving forward in business.

This job is a good fit for companies that have a huge amount of data to be analyzed. As a data engineer, you’ll be required to set up data infrastructure for the company. This organized data will be utilized by high-authority personnel to devise strategies in terms of moving forward in business.

Data Scientists in the Data-Driven Company

In companies where the main product actually is their data, machine learning is quite intense. In such companies, instead of answering to data-related questions, you as a data scientist will be responsible for applying your statistics, physics, R language, and mathematics background to “produce” exceptional data-driven products.

Data Generalist

Data generalists are mostly hired by reasonably-sized, data-driven yet non-data organizations in which other data generalists are a part of the team. Such companies give significance to data but these are not considered data-oriented companies. As a data generalist, your responsibilities may include conducting performance analysis, data visualization, and touching production code. However, the main objective of such companies is to fill a vacancy in this niche.

Though data science offers in-depth career paths that may also look too complex to a beginner, the following competencies are all the skills you require to get hired as a data scientist.

Non-Technical Skills Required

Working as a data scientist goes beyond learning data-related technicalities. Before entering the workforce, be equipped with some non-technical skills such as business acumen, intellectual curiosity, and communication skills.

With advancements in IT careers, data scientist jobs are the rage these days. Though being a data scientist can be a great career move, it’s pertinent that you build your core competence in this workflow by learning the above-mentioned skills. Before moving forward, it is essential to spend some considerable amount of time in learning R. Once you are good with the basics, you’ll most likely be able to learn other data science tools too.

Libby Stephens works as a graduate recruitment consultant. Her articles discuss a range of up and coming career opportunities that you may not have considered.


  1. The article is very informative and well-written. I learned a lot about data scientist.
    this article is really useful for me. thanks for sharing this article.
    Interested in learning data science and becoming a data scientist? Engage in real-world projects designed by industry professionals.

Leave a Reply to Daniel Cancel reply

Please enter your comment!
Please enter your name here