Data science is all about finding and combining the right set of tools best suited to get the job done. Data science gives companies and stakeholders the ability to make informed decisions and solve data problems. It is all about the extraction of knowledge from data to answer a particular question. Data science is one of the most competitive fields globally and one that requires to constantly upgrade your skillset. To pursue a career in data science, let’s take a some of the top skills required for a data scientist.

Statistics 

A data scientist’s primary job is to collect, analyse and interpret large amounts of data and produce insights for a company. So statistical skills play a significant role in your job description. You should be familiar with these skills for a data scientist, which are statistical analysis basics, including statistical tests, maximum likelihood estimators, distribution, etc. You should also understand which statistical techniques are not the right approach for a given data.  

Programming

Programming for a data scientist is working with application development, data management, application testing, etc, making programming skills a must-have tool in your repertoire. The most commonly used languages for programming is Python, and R. Python’s capacity for statistical analysis and easy readability makes it the most used. R makes problem-solving very easy with packages like Ggplot2, Esquisse, etc. R is viral in academic circles, while Python is becoming more famous in the data science industry.

Machine Learning

Machine Learning enables machines to learn a task from experience without explicitly programming them.  You need to be familiar with supervised and unsupervised machine learning algorithms. You don’t need an expert for Machine Learning algorithms since most of them are implemented using Python and R libraries. However, you will need expertise to understand which algorithm should be used based on the type of data you have and the task you are trying to automate, making these significant skills for data scientists.

Deep Learning

Deep Learning is a subdivision of Machine Learning, usually used for more complex applications. If you want to learn the deeper complexities of data science, Deep Learning is the way forward. Recently, Deep Learning’s complex applications like Image Recognition, Natural Language Processing, etc. are becoming popular even in standard Machine Learning applications, making it necessary to know at least the basics of Deep Learning to become a data scientist.

Cloud Services

Basic understanding of cloud services is essential as several companies are now moving their data to the cloud. These moves could be to public or private clouds with Microsoft Azure and Amazon Web Services or other contenders. Most companies are also moving extensive data and analytics applications to the cloud. Therefore, cloud skills for data scientist are required to perform data analytics effectively.

SQL

SQL is a computer program that can give you deep insights into a database depending on your query. It plays a considerable role in the requirement of skills for data scientists.  SQL involves writing and executing complex queries to carry out analytical functions and change the database as required. As a data scientist, you must be proficient in SQL to access data quickly and work on it.

Database Management

A data scientist needs to know how to manage and process large chunks of data. Database Management comprises a group of programs that can edit, index and manipulate the database. Database Management for data science lets you define, retrieve and manage data in the database. It also enables you to control the data, the format, field names, record structure and file structure, etc. 

Data Visualisation

Data visualisation is a graphical representation of your findings. Visualisation gives the power to draft a story from the data and create a comprehensive presentation. Data visualisation is an essential skill – with it you can understand and learn more about the data under consideration and its vulnerability. The real value of data is well established and understood when visually portrayed.

Microsoft Excel

Microsoft Excel is the best editor for 2D data and a virtual platform for advanced data analytics. It allows you to make as many changes and save as many versions as you wish. Data manipulation is relatively easy with Microsoft Excel compared to any other program. Microsoft Excel even allows you to look-up the required data among numerous records.

Communication skills

To become an expert data scientist, you must be excellent at communication. As a data scientist, it is your job to understand data better than anyone else and “translate” your findings to help the non-technical team make informed decisions. Communication skills will help you present the data in an effective and efficient format and better convey your findings and results. 

At Virginia Tech, we offer a comprehensive Certificate Program in Business Analytics & Artificial Intelligence course that will help you improve your skills as a data scientist. Visit our website for more information!