Are you looking forward to learning all the essential skills required to become a data scientist? Data science has gradually gained prominence because more and more organizations are moving towards leveraging the real power of data. Data is a key element for generating actionable business insights.
The most important data science skills include a mixture of core and tool skills. While you would need to learn Python coding, you must also have sound business understanding. Data science is an exciting discipline and presents some exciting career opportunities to all students and existing professionals. It helps generate insights essential to make marketing and business strategies, predicting patterns, and explore new business opportunities.
In this blog, we will discuss some core skills that will help you become a skilled data scientist. Core skills are essential as they help you make job-ready and explore your potential. Also, core skills are essential for adaptability.
Essential skills required to become a data scientist
- Business understanding
You must have a business understanding to get hired as a data scientist. It is essential to know how the industry works, how customers behave, and what trends are currently prevailing.
Let’s try to understand this with the help of an example.
An apparel company is noticing a decline in its sales, and they hire you as a data scientist. They want you to figure out the reason and provide a solution. Do you think you will be able to work without the knowledge of the industry?
You must have a sound understanding of the industry, how your competitors operate, how e-commerce stores like Amazon are affecting sales, etc. Just the knowledge of Python programming will not be enough. The role of a data scientist is much beyond using Python coding for data mining.
For you to solve a business problem, you will first have to understand how a business operates.
Another question you might encounter is how you can gain domain knowledge. You can try to pursue a specific degree that helps you build a solid understanding of the fundamentals of the industry. Let’s suppose you want to be a data scientist in the finance domain. You can pursue a degree in economics or any related field, which allows you to understand balance sheets, accounting, macroeconomics, microeconomics, etc.
The second way to gain business understanding is by working in a particular industry. Working in an industry will allow you to get exposure to the way things operate in an organization. Also, you will get a chance to interact with various individuals who will help you understand things in a better way. Once you start interacting with people, you will have to ask the right set of questions to understand the pain points of people. Moreover, you will always have to be curious to learn and know new things.
For example, for the retail sector, you will have to understand why websites like Amazon are taking away the market share from brick-and-mortar stores. Moreover, what are the current patterns of the industry? You have to be curious to explore all these questions and analyze data accurately.
- Analytical thinking
As a data scientist, you will have to be proficient with various tool skills. Therefore, you will spend time learning SQL, Power BI, etc. You will also spend time learning Python coding, and other tool skills.
But being aware of all these tools will not just be enough. You must be aware of which tool skill to use for a particular situation. Also, you must know how to use a particular tool to solve a business problem. For the same, you must possess great decision-making and problem-solving skills.
Let’s consider an example to understand this problem better. We will consider our old example of declining sales for a cloth business. You notice declining sales in a particular region because of a competitor. You can do a simple analysis in Microsoft Excel and study data to solve this problem. It will provide you with an accurate solution to your problem. You need not build high-level machine learning algorithms to solve the problem. Therefore, it’s essential to know which tool to use for solving a problem.
Critical thinking can be considered a sub-set of analytical thinking which allows you to look at a problem from different angles. It is essential to analyze a problem from different perspectives.
Often data scientists spend time learning complex programming and ML frameworks. But you need to understand that core skills are equally important to excel in the domain.
- Communication skills
As a data scientist, you will get involved in data crunching and analyzing data from various years to generate insights. But will those insights have value if you can’t communicate them effectively to other business stakeholders? Therefore communication skills along with presentation skills are equally essential to become a skilled data scientist. Effective communication is essential to solve pain points.
For presentation, there are some simple tips you can use to improve your communication and presentation skills. Use PowerPoint presentations more often to improve the effectiveness of your presentation. In PowerPoint presentations, there are some simple tips such as using a dark background and using simple text which is appealing to the eye. You can also use some storytelling skills to present your insights in a better way.
These are the three essential skills required to become a data scientist. Data scientists require a diverse skill set to operate properly in their industries. Their prominence is increasing due to the increasing prominence of data in different organizations. However, just note that since there’s a huge demand for data scientists in the industry, becoming one is equally tough. But if you move in the right direction and acquire all the skills properly, becoming a data scientist will never be challenging.
If you are interested in building a data career, you can refer to online resources that help you learn and practice all the skills properly. Nowadays, for fields like data science, you can find plenty of online courses that help you learn all the concepts simply and intuitively. Moreover, a good course will also focus on involving simple understanding and relatable examples that make the learning process engaging and fun. The course will also include data analysis projects with Python, which you can practice for better understanding. Moreover, all these things are also going to be essential to reflect on your resume. Often while applying for job interviews, these certifications, project experience, and domain knowledge can help in creating a positive impression in front of the recruiter. Look for such courses as they will help you save time, energy, and effort! They will help you become a skilled data scientist!