Trying to decide whether to expand your already strong analytical skills by getting a master’s in statistics or attending that intensive data science boot camp? Here are some pros and cons for considering a Data Scientist career.
Demand and Supply
LinkedIn reports a 56% increase in data scientist job openings in the U.S. over the past year. Indeed has more than 4000 data scientist openings nationwide. There are many jobs in many locations across many industries searching for the scarce data scientist. The data scientist skill set that requires great analytical skills, strong computer programming, data cleaning expertise and good communication skills is hard to obtain and so equally hard to find. The tightening of the H1b process has reduced the number of viable candidates for companies as well.
Compensation
Strong demand coupled with short supply leads to upward pressure on starting salaries. After a couple of years of experience data scientists can be earning in the $100K range. Add a few more years and some management experience and salaries from $120K to $160K are not unusual.
Interesting
Mike West, a machine learning evangelist on Quora.com, said, “I work with insanely smart people. I’m constantly learning.” Because of the evolving nature of the work there is always some new technique or some new software application to try or to implement. Colleen Farrelly, Data Scientist, said in the same Quora.com Q&A, “Getting to work on a lot of cool, disparate projects that provide ROI to the business and the customers using a variety of methods. Adding value and figuring out a hard problem are very rewarding.”
Growth
Data continues to grow and multiply exponentially. Tools to analyze that data continue to become more sophisticated and address more applications. That won’t be changing in any future anyone is imagining right now. Utilizing data, massive amounts of data, and the tools to analyze it define the data scientist career. There will be more jobs in more industries and longer career paths for almost anyone doing data science.
Blurry Job Definition
The data science field is evolving so fast that everyone’s definition of what a data scientist career means seems to be different. Often the people you work with don’t understand what you do or what you can do. HR and hiring managers often hire a data scientist for a software engineering or business intelligence role, leading to job turnover and confusing hiring practices. Individuals entering a company as the first data scientist need to be ready to define and champion their role to be effective.
Data
While the amount of data available is driving the need for data scientists, the amount of data available is overwhelming the data scientist, too. Cleaning, organizing and having the computer power to analyze immense amounts of data is an on-going challenge in the data scientist career. Data privacy ethics is an evolving field that impacts the work and effectiveness of the data scientist.
Mastering Data Science
Because there are so many applications, software, different data sources in the data science domain, it is impossible to be the master of all of them. Yet, companies latch on to the latest application and want it in every candidate, whether the company needs it or not. Developing the best data scientist career means picking and choosing which domain knowledge is essential to your success. Not easy to discern in the current go-go growth and evolving marketplace.
