Few doubt the demand for qualified and skilled data science pros is skyrocketing. The LinkedIn 2018 Workforce Report said,
The US is running a shortage of as many as 151,717 data science professionals.
As all kinds of industries around the world come to depend on data for competitive advantage, the demand for these professionals will further spike.
Despite the rising demand, the supply of professionals with adequate skills and knowledge in data science is lacking. One of the many reasons is knowledge-gap.
Who can look for a data science job?
What do recruiters look for when hiring a data scientist?
What are different types of data science careers?
What skills would you need to get a job in data science?
How do you begin your job search for a data science career?
These and many such questions remain unanswered and create confusion, thereby inhibiting candidates from even entering the industry. Cutting through the clutter, here is a quick glimpse into the industry.
Can you opt for a data science career?
So long you have the passion for data, and you know your craft, you can opt for a career in data science. That said, it will help you if you have the knowledge of Business Intelligence, Computer Science, Mathematics, Statistics, or Physics.
If you possess the passion for the career and have a foundation equipped with these subject matters, you begin your efforts toward carving a data career by first knowing the types of roles a data science professional can play.
A data scientist is different from a data analyst, and both differ significantly from data engineers. Let’s have a quick look.
3 Popular Data Science Careers
- Big Data Engineer
About the job: Data Engineers are the masters of several programming languages.They develop, test, and maintain data pipelines and ETL processes. They assist data scientists in ensuring their engineering can handle the ML models developed by data scientists. To data analysts, they lend their help in ensuring that data assimilation is accounting the desired metrics and sources.
- Big Data Analyst
About the job:This is among the most in-demand data science career. Data Analysts craft and answer the questions to drive new insights and revenue. They have analytics skills along with basic know-how of statistics. They navigate between the tech and business side making presentations and getting to the root cause of consumer behavior.
- Data Scientist
About the job:Data Scientists are a technical and analytical step above than other data career roles. Data Scientistsperform complicated modeling and work on advanced algorithms. They have a strong grip on mathematics and statistics.
Beginner-level Job Titles
Data Engineer: Big Data Developer; Technical Lead; Tableau Engineer; Data Architect; Software Engineer; Data Engineer
Data Analyst: Business Intelligence Analyst; Data Analyst; Project Associate; Modelling Analyst; CxO; Product Analyst; Product Manager
Data Scientist: Data Consultant; Research Scientist; Machine Learning Expert; Principal Data Scientist; Senior Data Scientist
How can you get in?
To get in the data science career role of ‘data engineer’ you must have the knowledge of major programming languages – especially JAVA and Python. As you rise in seniority, you will need to master the skills needed in the job role (check below). Further, you can get certified to prove your professional expertise in the industry. Leverage communities like KDnuggets to hone your knowledge.
To get in the data science career role of ‘data analyst’ you must have the passion as well as knack for digging out the meaning behind datasets.An industry-led data science certification can strengthen your candidature for the analyst job profile.
For data science, career role of ‘data scientist’ a Computer Science or Mathematics degree is usually demanded. Other than that, you must have a strong knowledge of both data engineering and analyst roles. In this job role, experience and domain expertise overshadow other credentials. An industry-led data science certification can highly improve your job prospects at large organizations. Certification can be your hallmark for lifelong learning and competence.
Irrespective of the type of career that you choose in data science, you will need to skill-up yourself. Here’s a quick table to size your skills.
Getting ready –Skills you need
| Data Engineer | Data Analyst | Data Scientist |
| · Relational Database Design and Programming
· JAVA · Python · Pig · Spark · Hadoop · Hive · C++ · MapReduce · Visualization Tools |
· SQL/Database Programming
· Financial Analysis · What-if Analysis · Predictive Analytics Models · Business Writing · Presentation Skills · Communication Skills · Excel Skills (Advanced) · Visualization Tools |
· Statistics
· Mathematics · Machine Learning · Artificial Intelligence (AI) · Natural Language Processing · Signals Processing · Visualization Tools |
