What is a Data Scientist?
The role of data scientist has been ranked 2016’s Best Job in America by the career website Glassdoor. With a median base salary of $116,840 and more than 1,700 job openings, it’s no wonder that data science is an attractive field. To better understand the high demand for data scientists, it helps to know how they are necessary to today’s tech world, what the role entails and how to go about securing a job in this field.
Making Sense of Rapidly Accumulating Data
The digital universe doubles in size every two years. By 2020, it’s estimated that the data we create and copy each year will reach 44 zettabytes (44 trillion gigabytes). With all this data comes the need for analysis and interpretation; data scientists help fill this need by helping businesses gain value from the data.
Because this field is still evolving, so is the definition of data scientist. Data scientists extract knowledge or insights from both structured and unstructured data, organize the data and present findings to team members, business leaders or clients.
While a data analyst is also able to extract information from large data sets, a data scientist takes it a step further—manipulating data to uncover deeper insight and even make predictions for the future. Data scientists realize that data always has meaning. They know how to solve a problem and use the correct tools to do so. They understand the infrastructure in place in order to deliver effective solutions.
A data scientist’s daily tasks may include:
- Basic exploratory data analysis and warehousing
- Data cleaning (also known as cleansing or scrubbing)
- Machine learning and statistics
- Creating visualizations
- Presenting analyses
- Extracting or transforming data
Of course, tasks vary depending on which company you work for:
- General Electric (GE): A data scientist here may help maintain assets or build models and run models to make predictions.
- Playstudios Gaming Firm: They may manage a series of dashboards that tell the company what users are doing, then analyze the data and create visualizations.
- Facebook: Data scientist at Facebook often contribute to enhancing the user experience.
Becoming a Data Scientist
To begin a career as a data scientist, it is important that you have a deep understanding of math, statistics, computer science and machine learning. A bachelor’s or master’s degree in this area will help you solidify those skills and learn to translate them to this functional area. If you are naturally inquisitive and have a penchant for problem solving, that can be helpful too.
You may find data science jobs available within the company at which you currently work, on a school job board, through a recruiter or on a career website. To help data scientists connect with employers, websites such as Correlation One have recently launched. The site offers nonacademic tests that are created and graded by the company’s own data scientists and those on its advisory board. The results are then shared with employers to help fill roles. As the profession grows, there could be a rise in similar platforms.
When it comes to a data science job interview, it’s good to ask specific questions regarding the company’s data—how organized it is, which solutions are in place to manage it, whether there are set budgets to do so, etc. This can help avoid putting yourself in a position where you are suddenly expected to make sense of data that is extremely unorganized.
The career outlook for this field is very strong. McKinsey reports that by 2018, the U.S. could experience a shortage of between 140,000 and 190,000 people with deep analytical skills, along with 1.5 million managers and analysts who can effectively analyze big data. It is likely that job prospects will remain strong for data scientists in the coming years.
If becoming a data scientist is of interest to you, take the first step on this career path by learning more about about data science degree options.