Skills Needed to Be a Data Scientist or Analyst

Statistics and engineering are two educational fields that are pursued by Data Scientists. A Data Scientist is often termed as a Data Engineer or Analyst. Tech pros showing a keen interest in mathematics tend to be more successful as a Data Scientist. The job role of a data scientist depends on the requirements of the company that he chooses to work with.

Data scientists are known to pursue higher education – more than 80% of them possess a degree in Masters, while over 45% of them possess PhDs. A sound academic background is usually necessary for being a data scientist. Data scientists comprise of students pursuing Engineering (16%), Computer Science (19%) and Statistics and Mathematics (32%).

Professionals possessing in-depth knowledge of certain analytical tools like R and SAS are preferably chosen for the position of data scientist or data analyst.

A data scientist needs to acquire some of the following technical skills:

Python – Python is considered to be an important coding language for data scientists alongside C++, Perl and Java.

Hadoop – Hadoop remains high on the list of preference for HR managers looking for data scientists. Possessing work experience on Pig or Hive could just be another strong USP for these professionals. It could even be beneficial for them to gain expertise on cloud tools besides acquiring knowledge on other relevant coding languages.

SQL Database or Coding – NoSQL has turned out to be one of the key components of data science besides Hadoop. However, a data scientist is still required to develop SQL of complex nature at times.

Unstructured data – Regardless of whether you’re considering audio, video feeds or social networks, data scientists are usually not expected to handle unstructured data. 

 Non-Technical Skills

Intellectual curiosity – This phrase is commonly associated with data scientists and is seen everywhere. You’ll gain more insight into this while checking out soft skills. You may come across a few guest blogs depicting posts on this topic.

Business development – You must gain a better understanding of the entire industry in your attempt to be a data scientist. In doing so, you must understand the key business objectives of your company. For a data scientist it’s truly important to identify the critical problems experienced by a business and how the problems can be resolved. It will help you find new means to leverage business data. 

Communication skills – Data scientists that can identify crucial technical faults and resolve them are highly sought after by development companies. Analysts that can communicate their technical findings to the non-technical divisions like Sales and Marketing departments. All companies want their data to be utilized properly.

You’re bound to acquire useful information on becoming data scientist while doing a quick search. You won’t need to gather all of such information instantly. You may begin by pursuing a big data certification and then acquire necessary skills gradually. It will eventually help you in shaping your career in the right direction.

19 Feb 2016