What are the skills needed to become a Data Scientist
They are in brief
- Python Coding
- SQL coding
- Machine Learning and AI
- Data visualization
- Unstructured Data
- Communication skills
Data scientists are highly educated , most of them have a Master’s degree and a few of them have PHDs and If a person holding Graduate ship , he is eligible to become a Data scientist – and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist. To become a data scientist, you could earn a Bachelor’s degree in Computer science, Social sciences, Physical sciences, and Statistics. The most common fields of study are Mathematics and Statistics (32%), followed by Computer Science (19%) and Engineering (16%). A degree in any of these courses will give you the skills you need to process and analyze big data.
Well versed knowledge of at least one of these analytical tools, for data science R is generally for Data Scientists. R is specifically designed for data science needs. You can use R to solve any problem you face in your area. In fact, nearly half of data scientists are using R to solve statistical problems.
Python is the most common coding language using for Data science at all times Because of its simplicity and versatility, you can use Python for almost all the steps involved in data science processes. It can take various formats of data and you can easily import SQL tables into your code. It allows you to create datasets and you can literally find any type of data set you need from internet.
You need to be proficient in SQL Query to be a data scientist. This is because SQL is specifically designed to help you access, communicate and work on data. It gives you insights when you use it to query a database. It has concise commands that can help you to save time and minimise the amount of programming you need to perform difficult queries. Learning SQL will help you to better understand relational databases and boost your profile as a data scientist.
Machine Learning and AI
A large number of data scientists are not proficient in machine learning areas and techniques. This includes neural networks, reinforcement learning, adversarial learning, etc. If you want to stand out from other data scientists, you need to know Machine learning techniques such as supervised machine learning, decision trees, logistic regression etc. These skills will help you to solve different data science problems that are based on predictions of major organizational outcomes.
The business world produces a vast amount of data frequently. This data needs to be translated into a format that will be easy to process. People naturally understand pictures in forms of charts and graphs more than raw data. An idiom says “A picture is worth a thousand words”.
As a data scientist, you must be able to visualize data with the aid of any of data visualization tools such as Matplottlib, and Tableau. These tools will help you to convert complex results from your projects to a format that will be easy to comprehend.
It is critical that a data scientist be able to work with unstructured data. Unstructured data are raw data that does not fit into database tables. Examples include videos, blog posts, customer reviews, social media posts, video feeds, audio etc. They are heavy texts lumped together. Sorting these type of data is difficult to manipulate because they are not streamlined.
Non Technical skills
Curiosity can be defined as the desire to acquire more knowledge. As a data scientist, you need to be able to ask questions about data because data scientists spend most of their time to prepare their data. This is because data science field is a field that is evolving very fast and you have to learn more to keep up with the pace.
You need to regularly update your knowledge by reading contents online and reading relevant books on trends in data science Curiosity is one of the skills you need to possess for being a data scientist.
skills you need to possess for being a data scientist.
To be a data scientist you’ll need a strong understanding of the industry you’re working in, and know what are your problems to solve. In terms of data science, being able to discern which problems are important to solve for the business is critical, in addition to identifying new ways the business should be leveraging its data.
For instance, presenting a table of data is not as effective as sharing the insights from those data in a storytelling format. Using storytelling will help you to properly communicate your findings to your employers. So you should be proficient to present the things in the form of story telling
When communicating, pay attention to results and values that are embedded in the data you analyzed. Most business owners don’t want to know what you analyzed, they are interested in how it can impact their business positively. Learn to focus on delivering value and building lasting relationships through communication.
It is a teamwork You will have to work with different category of people at different times like company executives to develop strategies, work product managers and designers to create better products, work with marketers to launch better-converting campaigns, work with client and server software developers to create data pipelines and improve workflow. You will literally have to work with everyone in the organization, including your customers.
If you are really interested in this area to become a Data Scientist,
Here is a test through which you can check whether you are fit to be a Data Scientist