Roles of Data Scientist
Who is Data Scientist?
Data scientists are big data creators, who analyze large sets of structured and unstructured data. A data scientist’s role combines computer science, mathematics, and statistics.
Data scientists analyze, process, and model data then they elucidate the results to create practical plans for companies and other organizations. A data scientist work usually involves of making the correction of noisy unstructured data, from sources such as social media feeds, smart devices, and emails that don’t neatly fit into a database.
Data Scientist Role and Responsibilities:
We have mentioned down the six knowledge points which are a must for every Data Scientist. They are as follows:
(1) Statistical skills: Data Science skills is all about decoding the basic insights from the data sets, which involves a strong directives over statistics. A proficiency over core statistical concepts like Linear Regression, Time-series Analysis and Non-straight regression are also typical attributes of a Data Science.
(2) Mathematical skills: Some of the mathematical ideas like Multivariate Calculus, Liner Algebra, and Probability theory form the basis for Data Science. Some of the Data Scientist have a good knowledge about Applied Mathematics which helps them to avail through their role with more ease.
(3) Programming skills: It It is often said that for a gratifying career in Data Science, you must have a strong computing mindset and the ability to understand codes. R programming language is used in most of the statistical problem-solving in Data Science. Also Python is widely used language in Data Science and is relatively simpler to use and write down.
Python can also be used across a huge dataset and also in creation of data sets. More than half of the world’s Data Scientists attest for Python as the creation for executing data analysis projects.
(4) Participation in the real-world events: As there are lot of hackathons today and also, coding seminars, data science meets organised by leading companies and also various events to groom young talent and also search for the best. Participating in such events will not only help you to network easily but also widen your knowledge to face real-world challenges.
(5) Comfort with the unstructured data: Data Scientists have to work with the huge amounts of data, most of which is also unorganised. There are many software and tools such as NoSQL, Apache, Hadoop, to handle unlinear data and a data scientist should be able to handle them very well.
(6) Data Storytelling: To be able to present your perception is very important as being able to handle to derive these insights. Data Scientists who are expert at this present their finding through Data Visualisation techniques and also work the insights into a story that is crisp, engaging and relatable to everyone involved in the decision making process.
Job Roles in Data Science:
1. Data Analyst
Data analyst are responsible for a variety of tasks including visualising, and processing of large amount of data. They have to execute queries on the databases from time to time. One of the most important skill of a data analyst is an optimization of the data. This is because they have to write and modify algorithms that can be used to kill information from some of the biggest databases without corrupting the data.
2. Data Engineers
Data engineers test and build a scalable Big Data ecosystems for the businesses so that the data scientists can run their algorithms on the data systems that are stable and highly optimized.
3. Database Administrator
Job profile of a database administrator is more easily understandable and they are also responsible for the proper working of all the databases of an enterprise and grant or revoke its services. They are too responsible for database backups and recoveries.
4. Machine Learning Engineer
ML engineers are very much in high demand today. ML engineer is expected to perform A/B testing, build data pipelines, and implement common machine learning algorithms such as classification, clustering, etc.
5. Data Scientist
Data scientists has to be able to understand and digest the challenges of business and offer the best solution using data analysis and data processing. They are also expected to perform predictive analysis and run a fine-toothed comb through an “unstructured/disorganized” data to offer actionable insights.
6. Data Architect
A data architect generates the plan for data management so that the databases can be easily integrated, and protected with the best securities. They also make sure that the data engineers have the best tools and systems to work with.
7. Statistician
A statistician, has a sound understanding of statistical theory and data organization. Not only they extract and offer valuable insights from the data clusters, they also help to create new methodologies for the engineers to apply.
8. Business Analyst
The role of business analysts is lightly different than the other data science workers. They are good at understanding that how data actually works and how to handle large volumes of data, they also separate the high value data from the low value data.
9. Data and Analytics Manager
A data and analytics manager see the data science operations and assigns the duties to his team according to the expertise. Team’s skill should include technologies like SAS, SQL, R etc. and of course management.
Hope you found out this blog informative….!!!!
This information is contributed by:
Rutuja Bankar, Amruta Potdar, Aditya Sadamate and Vaibhav Vairagade.
