Data scientists–named the no. 1 best job in America by Glassdoor for the past three years–are expected to remain in high demand for 2019, as nearly every company requires employees who can effectively analyze data and organize it into business insights.
Companies have been aggregating data for years to help them make better decisions, said Patrick Circelli, regional recruiting manager for the West Coast at IT recruiting firm Mondo.
“Data scientists have unique critical thinking skills, excel in visualization, and help to understand future-based insights for any industry and any business,” Circelli said. “Whether that’s a consumer-based good or a highly functional business software, they want to translate as much of their enormous data sets into actual intelligence to make informed business decisions about how to improve experiences, drive user actions, and so much more.”
SEE: Job description: Data scientist (Tech Pro Research)
Data scientists tend to come from broad backgrounds, often in math or statistics, Circelli said. Certifications and degrees can help these professionals or those entering the field drill down into more specific areas, like big data engineering, or using predictive analysis for marketing purposes.
“Specific specialization areas can help mold their critical thinking skills into the avenues they see most beneficial for their careers,” Circelli said. IT certifications can also greatly increase your salary, according to a Global Knowledge report.
Like most other tech fields, data science is currently a candidate-driven market, Circelli said–there are a ton of openings across all industries, but not enough skilled candidates available to fill them.
“Employers and hiring managers tend to be very selective about hiring for this skill set, since it is extremely important to the future of their business,” Circelli said. “It would be best for candidates to fully understand the role they are interested in applying for as much as possible up-front to ensure their specific area of data manipulation skills will be most useful to the employer’s needs.”
Here are four certifications data scientists can consider to boost their career and salary potential, according to Mondo.
SEE: The future of IT jobs: A business leader’s guide (Tech Pro Research)
1. Mining Massive Data Sets Graduate Certificate
This certification is important for gaining the fundamentals of data mining, which is the start to the data science process, Circelli said.
“While it can be an expensive course with larger universities, it is one of the most important to take into consideration given that it helps talent develop core data mining skills,” he added. “After all, how can you manipulate data if you can’t even understand it? Once you’re able to aggregate data effectively, then you’ll be able to manipulate the data to best serve your needs.”
2. PGP in Big Data Analytics and Optimization
This hands-on course can be completed on nights and weekends–a huge plus for working data scientists and other professionals, Circelli said. The course specializes in coding various data manipulation programming languages, like Python and R, which can be used in ecosystems like Hadoop and Spark.
“It also helps highlight how to best manipulate data using code with a hands-on approach versus a more conceptual approach that you’ll find with other certifications,” Circelli said.
3. Cornell Data Science Certification
This certification demonstrates skills in using predictive data analysis as a marketing tool. “This certification is awesome because it has so many different areas available for you to choose from in terms of what you want to focus in, from Business Analytics to Data-Driven Marketing,” Circelli said. “So you can truly specialize and build the niche skills for the area you want to focus in. It’s also more affordable than other certifications, but definitely still an investment.”
4. Hortonworks Certified Associate (HCA)
This is a more beginner-level associate course that specializes in hands-on experience with industry-standard data manipulation tools like Hadoop, Spark, Pig, Hive, and Solr to help build fundamental skills, which can translate to a variety of data science roles, Circelli said.
“Since there are so many different certifications out there, you can get very specific to the specialized skill development you need,” Circelli said. “I will say the primary con is these certifications tend to be expensive, but are always worth the investment.”
