How to become a successful data scientist? Here’s how!

Now that the big data era is here, every data-driven organization has started looking for qualified data scientists- preferably ones with data science certifications- because organizations today want to leverage advanced techniques and relevant tools to leverage data that they gather. There’s no denying that the data science industry is flooded with data scientist jobs these days, but to land a dream job as a budding data scientist or even if you’re an amateur in this space, here’s how you can become start from scratch to get your perfect data scientist job -



  • Brush up your statistics and mathematics skills- wither by learning or a data science certification. A good data scientist should be able to understand the relevant big data algorithms and analytics to unlock the maximum potential of data science. Through data science certification, candidates can comprehend big data solutions easily.
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  • It has become imperative for the budding data scientists to broaden their horizons in data science and big data- and machine learning is one such aspect of big data analytics that every data scientist job includes. Data science industry is constantly evolving- so are advanced tools and techniques related to big data analytics- it has become important for potential data science candidates to get certified in any data science certification to gain expertise in the data science space.
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  • Coding is also one such factor to get your dream data scientist job. Manipulating codes is one of the primary roles that data science industry looks for in a potential data science job candidate. Begin with an open source programming language like R or Python.
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  • Basic understanding of data lakes, distributed storage and databases. Every data science industry is looking for candidates with expertise and skills so that they can decode how these repositories are made and can use, analyze and access data.
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  • Learn data cleaning and data munging techniques. Data munging can be described as ‘transforming raw data into different formats so that at a later point of time, it is easier to derive valuable insights from it’. However, data cleaning eliminates bad data and duplication of datasets. These two are considered as the most essential tools in the box of data analytics scientists.
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  • Understand the basics of reporting and good data visualization. There is no need to become a graphic designer- all you need to do is learn how to create and manage data reports- that everyone in the organization can comprehend.
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  • To add more skills in your resume, all you need to do is escalate your level and start learning how to use Spark, R and Hadoop. Experience and knowledge of these tools and techniques can help you get through many job applications- you can always sit back and decide which one to take and which one to leave!
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  • Becoming a part of data analytics community is also important. Follow and try to learn from the thought leaders from the industry. Read their blogs, engage yourself, ask questions and stay abreast of latest tools and techniques to make your mark!

3 comments

  1. The information shared by you was very helpful in getting more insights into career in Big Data. Well explained!

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  2. A well researched article about data science certification and i assume everyone will agree with this. Already added in my favorites.

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  3. Yes, well said. Big data is one of the best career and this article shares a lot of useful information. Thanks for posting.

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