Top 10 Recession-Proof Data Science Skills to Master in 2023
The article presents the top 10 recession-proof data science skills to learn in 2023
Data science has become the most essential part of many industries today, given the massive amount of data that is produced it is one of the most debated topics in IT circles. Data science is an interdisciplinary field that applies scientific methods, processes, algorithms, and systems to find unseen patterns, derive meaningful information, and make business decisions. It uses complex machine-learning algorithms to develop predictive models. Its popularity has grown over the years, and companies have started adopting data science techniques to heighten their business and increase customer satisfaction. But during an economic downturn, there is no guarantee that any skill is entirely recession-proof, while there is some good news: according to research from Harvard Business Review and Emsi Burning Glass, employers are placing more emphasis on recession-proof Data science skills rather than degrees when it comes to hiring. Here the article presents the top 10 recession-proof Data science skills to pick up your career in 2023.
Data analysis
If someone ever desired to improve business processes and make strategic decisions for the organization, there is a need to understand and perform data analysis. Data analysis, or extracting insights from clean data involves using tools, and statistical techniques and drawing from many fields like mathematics and computer science. But surprisingly, many workers lack the capabilities to perform some basic analysis which indicates there is a shortage of workers with data analytics skills. Learning this skill will surely make your career recession-proof.
Knowledge of SAS and Other Analytical Tools
Knowledge of analytical tools is a helpful data scientist skill for taking out valuable information from an organized data set. SAS, Hadoop, Spark, Hive, Pig, and Rare are well-known data analytical tools that data scientists use. Certifications can be helpful in establishing your expertise in these analytical tools and help you gain this valuable data scientist skill.
Programming
You need to have an understanding of various programming languages, such as Perl, C/C++, and Java for a data science role. These programming languages help data scientists organize unstructured data sets. This is among the top recession-proof Data science skills to boost your career.
Adept at Working with Unstructured Data
Data scientists should have an understanding of handling unstructured data that comes from different channels and sources. For example, if a data scientist is working on a project to help the marketing team provide insightful research, the professional should be skilled at handling social media as well. Some other data science skills required are knowledge of Machine Learning, Artificial intelligence, Deep learning, Probability, and Statistics.
Machine Learning
Machine learning is the backbone of data science. Data Scientists requires to have a strong grasp of machine learning in addition to basic knowledge of statistics. Developing machine learning expertise needs specialized knowledge in mathematics, programming, and artificial intelligence.
Python and R
Python and R are well-known programming languages for data science professionals. While the R language is more specialized, Python is a general-purpose programming language designed for a variety of use cases. Python is generally considered as easiest language to learn and is broadly applicable. This is among the top 10 recession-proof data science skills to boost a resume.
Data storytelling
Communicating insights from data to stakeholders is mandatory to have skills for both data and experienced business professionals. Knowledge of tools such as Tableau or Google Charts is a must-have to improve decision-making and answer questions about past performance.
Statistics
Statistics is a crucial part of data science. Generally, statistics are used to describe insights pulled from big data and/or forecast and make predictions. Many core data analysis techniques such as regression, time series, and factor analysis fully rely on statistics.
SQL
SQL is among the most learned data science skills for 2023. This popular programming language helps to communicate with databases and extract data for application development, reporting, and analytics. It is a supreme skill for data science professionals and business leaders looking to conduct complex calculations and forecasts.
Excel
Spreadsheet tools like Excel can perform data manipulations, data processing, and even visualizations. If you are running short of time to perform complex data analysis, you may want to consider investing your time in learning Excel. This is one of the top recession-proof Data science skills.
