The fundamentals of data science – statistics, probability, and programming – are important to do well in a data science role. Those can’t be ignored. However, a few selected skills remain highly in-demand among employers than others.
For aspiring and seasoned data science professionals, learning these skills and mastering these skills, respectively will open more and lucrative opportunities. So what skills should you learn?
In-demand skills for data science professionals
Python:The programming language remains the most sought-after among employers. The ease-of-use and comprehensibility of Python makes it the prominent programming language in data science after R.
If you know R, learning Python will expand your skillset and open more job opportunities. Jeff Hale, reports, Python, is a requirement for 70% of total job listings found across Indeed, LinkedIn, Simply Hired, and Monster in the United States.
Pandas, Scikit, NumPy, and Keras are frequently used libraries that data scientists are expected to be strong at. The collective percentage amounted to roughly 15% of total job listings that listed these skills.
SQL: The use of relational databases is increasing among employers. Cloud-based databases are becoming increasingly common in the data science community, which need extensive knowledge of SQL to operate.
In Jeff Hale’s research, SQL stood as the third-highest in-demand skills in data science. Over 50% of data scientist job listings had SQL as a requirement. AWS (RDS), Mongo DB, and Cassandra are popular relational databases being used across the industry.
In Jeff Hale’s research, SQL stood as the third-highest in-demand skills in data science. Over 50% of data scientist job listings had SQL as a requirement. AWS (RDS), Mongo DB, and Cassandra are popular relational databases being used across the industry.
Hadoop: Synonymous in the Big Data space, Hadoop is an open source framework for distributed storage and processing of large datasets. Enterprises are building their data science operations around Hadoop. So it’s an essential to tool to learn for data science professionals. Given this, it’s not a surprise that many data science certifications check candidate’s proficiency in Hadoop.
Spark: This is another Big Data tool that has found extensive use in the data science industry. Jeff Hale’s research found that Spark was a mandatory skill for data scientists in nearly 30% job listings.
If you’re already a data scientist or learning data science, add Spark to the list of skills you need to learn to excel in your job.
Java: Java is the primary programming language for using Hadoop and Spark. Naturally, Java is an important skill for data science jobs. Extensive knowledge of Java, means strong command for Spark and Hadoop. Over 25% of job listings mention Java for data science jobs.
Tableau: Tableau is the most prominent data visualization tool used across the industry. Using Tableau, you create interactive and easy-to-understand graphs. Over 20% data science job listing seeks Tableau as a necessary skill.
Become a credible data scientist
Aspiring and experienced data scientists can increase opportunities by getting a data science certification.
Several organizations including DASCA, Microsoft, Dell, IBM, and Cloudera offer globally recognized certifications. Earning a certification provesyour skills and demonstrates your ability to work efficiently. With a certification, you will gain more attention of employers, but it’s not an alternative for projects.
Portfolio and practical experience are top qualifiers for all data science jobs.
