The Significant Job Roles in Data Science

By Jyoti Nigania |Email | May 18, 2018 | 5433 Views

Data science has created so much hype in the world of IT sectors that from big to small companies all are now hiring employees who have knowledge regarding this subject. The data science industry's job market is hot today. Data science is helpful for the employees to get understand about data and then make it in a proper way so that it can be communicated in a better way which is valuable for the companies. Diverse data science roles along with the skill set, technical knowledge and mindset required to carry it. Following are the different roles of Data Science in industries:

  • As Data Scientist:
A data scientist is undoubtedly one of the hottest job titles that can be put on business card. A data scientist gets to work every day with different mindsets of a curious data wizard. They are the master in this field and able to handle the raw data, analyzing the data with the help of different statistical techniques to share their useful insights to other persons in an organization. Google and Microsoft like big companies are demanding this profile. 

  • As Data Analyst:
The data analyst is the pilot of the data science team. Knowledge of other languages like R, Python, SQL and C are addition to their profile. Just like the data scientist, the skills and talents that are needed for this role are diverse and range the entire spectrum of the data science process combined with a healthy "figure-it-out" attitude. The big companies like HP and IBM are highly demanding data analyst. 

  • As Data Architect:
With the hype of big data, the importance of the data architect's job is speedily increasing. The data architect creates the plans for data management systems to integrate, centralize, protect and maintain the data sources. The data architect should be the master of technologies like Hive, Pig and Spark so that they will be on the top of every new innovation. 

  • As Data Engineer:
The data engineer loves to play with database and large scale processing systems as they have a background in software engineering.  They can easily control over the technologies and familiar with diverse set of languages that span both statistical programing languages and languages oriented more towards web development. Data Engineer is the jack of all trades.

  • As Statistician:
The data science also plays a vital role as a statistician. In this field one should have strong background in statistical theories, methodologies and logical mindset. Basically the statistician represents what the data science field stands for and extracting useful insights from the data hence they can handle all sorts of data. 

  • As Database Administrator:
"Data is the gold". This clearly states that need someone who extract that valuable mine. With the help of data administrator the data is available to all the user's and keeps it safe and secure. Also carrying the backup and recovery of the data and supports the entire function.

  • As Business Analyst:
 This term business analyst is little bit different from the rest of the filed. Here one should be master in linking the data insights to actionable business insights. They basically act as the intermediary between the business folks the techies. Companies like Uber, Dell and Oracle are looking such kid of profile.   

Conclusion:
Above mentioned are the different roles in the field of data science. All roles can only be performed with high skills and deep knowledge for particular job. This field is the highest paying amongst all the fields. While looking for the data science as a career one should consider all the roles and work according to their skill set. 

Source: HOB