Data scientists have been in high demand in recent years. Initially, only large enterprises made sizable investments in data, but that has changed significantly. As more organizations recognize the value of data and increasing amounts of data are harnessed, the growth in demand for data experts shows no signs of slowing down.
Organizations are becoming increasingly reliant on data-driven insights to develop business intelligence, acquire and retain customers, identify new business opportunities, and maintain an edge over the competition. This means greater numbers of data scientists are required every year. Additionally, more roles will likely be created in many organizations, such as data translators, who can bridge the gap between data scientists and the business.
What do data experts do?
Data experts analyze large datasets, identifying trends in vast quantities of data and looking for ways to use the data to build strong connections between businesses and customers. They also need to be able to work with unstructured data from a range of channels and sources, including social media.
High-performing data experts require a combination of skills and experience. They need a mind that is both creative and highly analytical. In addition to applying strong analytical skills, they will need to draw on intuition to pick up on trends in the data.
Skills required for data expert roles
- Familiarity with analytical tools
- Coding
- Communication skills
- Databases
- Data preparation
- Data visualization
- Deep learning
- Machine learning, including fluency in Python or R
- Statistics
For some roles, data scientists may also be expected to have fluency in other programming languages, such as SQL, NoSQL databases, relational database management systems (RDBMS) and Apache Spark.
Data scientists need strong communication skills so they can present findings to people in other parts of the business, many of whom will not have the same level of expertise in statistics. Presentations need to be accessible and engaging for colleagues or clients, who generally have a much more limited understating of data science.
Qualifications required for a career as a data expert
Data scientists usually have a background in computer science, a quantitative social science or statistics. A Master’s in Applied Statistics degree is one of the best ways to boost your career and access new opportunities for advancement in data management and more attractive compensation packages. With the accelerated online Master’s of Science in Applied Statistics program from Michigan Technological University, you can continue working and fit your studies around your work hours.
An entry-level data scientist in the US can expect to earn, on average, $97,462, according to figures from Glassdoor, while Indeed reports the overall average as $144,986 as of November 2022. The higher end of the salary spectrum can exceed $200,000 per year.
With the ever-growing demand for data scientists expected to continue, this is a very good time to embark on a course in statistics and progress your career in data science.
