Top Skills Needed for Your Data Scientist Career


by Rupesh on April 13, 2021
Precision Blog

Data science is constantly evolving, which means the skills needed to succeed as a data scientist are always evolving. Data science is one of the fastest growing fields with a high demand of skilled talent with the right aptitudes. In this blog, we narrow down the greatest skills needed for your data scientist career to gain new opportunities and to be successful.

Top Data Scientist Skills:

  1. Programming
  2. Analytics Tools
  3. Data Manipulation and Analysis
  4. Machine Learning
  5. Data Visualization
  6. Business Acumen
  7. Communication
  8. Data Intuition

These skills are very important to have in your data scientist career. Continue reading for a deep dive into each skill and what is needed to obtain them.

1. Programming
This may be one of the most obvious skills needed as a data scientist. It’s very important to have knowledge in many different programming languages, including Python, R, SAS, SQL, Java, C/C++, and more. These languages allow data scientists to organize unstructured data sets. The type of programming language you choose to use depends on the company and industry you are in. Once that is determined, you are able to move forward with learning and developing your skills within these tools.

2. Analytics Tools
Different analytics tools allow you to extract meaningful insights from organized data. You are able to sharpen your skills in different analytics tools through certification and other online tools. This is a very valuable data science skill and it’s recommended that you discover different online resources to broaden your knowledge.

3. Data Manipulation and Analysis
Data manipulation, or data wrangling, consists of cleaning data and transforming it into a format that can be easily analyzed. It builds off coding languages to address imperfections or missing values in the data. Data manipulation is time consuming at times, but it’s very beneficial. It helps you and your team create more accurate data-driven decisions. When it comes to data analysis, you are taking your data and learning from it. Analysis is one of the most important tasks of a data scientist.

4. Machine Learning
If you’re working for a company that handles a lot of data, you are likely using machine learning to tackle this. Machine learning is used to build predictive models, and it’s a good skill to have. It’s not always a required skilled to have as a data scientist, but it’s great knowledge to add to your repertoire.

5. Data Visualization
What’s the point of obtaining data if no one is able to understand what they are looking at? Data visualization is a highly needed skill. It typically requires using a data visualization tool to create graphs, charts, and other visualizations to help others understand the collected data, leading to proper analysis. Platforms such as Power BI, Tableau, and more are great tools to use for data visualization.

6. Business Acumen
Technical skills are very important to have in your data scientist career, but you should also obtain certain non-technical skills to be successful. It’s important to have an understanding of business problems so that you are able to distinguish issues and challenges that need to be solved for the business to grow.

7. Communication
Communication is another non-technical, soft skill that is needed for a data scientist to be successful. You must be able to extract and analyze data, but in order for it to be beneficial to your organization, it must be communicated to your team members who may not a have as a great as an understanding as you. Remember, communication is key.

8. Data Intuition
In some cases, valuable insights are not easily read in large data sets. This is where data intuition comes in. A highly skilled data scientist should have the intuition and knowledge to look beyond the surface for valuable information. This skill comes with training and experience and makes data scientists more efficient and successful in their work.

There are many technical and non-technical skills that are needed to be a successful data scientist. All of these skills can be achieved through certification, deep learning, experience, training, and more. If you have any questions about data and analytics or your next data scientist opportunity, feel free to contact us!

Sources:
https://www.springboard.com/library/data-science/technical-skills-for-data-scientists-2021/#skill-7-business-acumen
https://www.simplilearn.com/what-skills-do-i-need-to-become-a-data-scientist-article
https://www.analyticsvidhya.com/blog/2020/11/14-must-have-skills-to-become-a-data-scientist-with-resources/

About Precision
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