What is the role of a data scientist?

Apr 22, 2020
2 min read
what is the role of a data scientist?

Hiring a data scientist is a very good idea if you need help with handling and managing data of all kinds. This is a job that requires a lot of technical skills, more specifically mathematical and domain skills. The Data Scientist is that person that will study your data and he will then provide you with some insights on it. He can use the data to make predictions as well. The requirements for a Data Scientist will differ based on the domain or business. One thing to note about this job is that it’s the middleground between a data analyst and a machine learning engineer.

Requirements for this job

Normally, programming skills are always handy when you process a lot of data. However, this is not something mandatory, and you need to keep that in mind. Working with large data volumes is also a high point, so you may want to consider that at all times if possible. You want to know a lot of R and Python, as these are the languages that get used for solving tasks. Python in particular has a lot of new packages that work for Data Science tasks, so it’s really helpful.

A Data Scientist will mostly communicate with stakeholders, project and project managers, data engineers and machine learning engineers. The latter ones are very important because they will implement models based on data provided by the Data Scientist.

How does the working day of a Data Scientist look like?

This differs based on a variety of factors. But for the most part, the Data Scientist is known for working hard on a variety of solutions. He will do data analytics tasks at first. These means working with data, designing reports and then viewing all the data. He will also define the business needs for that task, which is really handy and convenient.

On top of that, the data scientist also has various data science tasks to complete every day. That means researching solutions for the task at hand, offering data preparation for the model (can eat up to 80% of the time), testing and training models, then picking the right one based on the needed metrics.

What tools are used by data scientists?

That depends on the situation. But for the most part, a data scientist will normally rely on SQL and NoSQL DB for example. On top of that, the data scientist also uses Tableau and other visualization tools. We already mentioned R and Python, which are extremely helpful. Lastly, the data scientist can use things like Tensorflow / Keras for Neural Networks, as well as sklearn, numpy, pandas or other ML packages.

Conclusion

At the end of the day, it’s easy to see why hiring a data scientist is a great idea. He gets to work with and manage things like artificial intelligence, machine learning and deep learning. Plus, a lot of data is generated every day. The data scientist needs to understand data and information, how it works and how it can be adapted to the company needs. Just take that into consideration, it’s extremely important to have a reliable data scientist as it will help push your business to the next level!

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