Data Science is a broad field with a large number of available career paths and degree specializations that lend themselves to those career paths. Identifying which degree path sounds most interesting to you is an important first step toward figuring out which career within the field you wish to pursue.
The most important thing to determine when selecting your degree path is the level of schooling you want to pursue. While a bachelor’s degree, master’s degree, or PhD can give you data scientist career opportunities, your degree level and degree type may limit which career opportunities are available to you.
Note that actual titles can vary a lot and the following is not a comprehensive list, positions pertaining to a master’s degree and higher are likely to be called a “Data Scientist.”
Bachelor’s degrees in statistics, economics, computer science, or more mathematically rigorous marketing and business programs, can give you access to more basic positions focused on visualization or basic analytics.
Key positions include:
Data Visualization Specialist: These individuals are experts at taking complicated statistical data and presenting it in a way that is useful to data scientists, as well as those who are not subject matter experts. This requires knowing how to properly access and analyze the necessary data and then translate it into useful information that allows for effective decision making.
Business Analyst: A business analyst utilizes information about sales, consumers, and industry conditions, along with statistical software, to identify and build strategies around market trends and increase business performance through sales and maximizing efficiency.
Graduate Certificates are a great way to build new skills in the data science industry. They allow for flexibility with online options, often less expensive tuition, and they generally require less time to earn than say a Master’s Degree.
Data Science is a vast, fascinating, and diverse field that is home to a variety of opportunities and access points. Finding the right degree program can be tough. Certificates are be supplementary to any field and can provide the right combination of statistics, programming, and predictive algorithms to succeed.
Master’s Degrees are typically required in order to gain access to positions described as “data science professionals.” These require degrees in statistics, economics, computer science, or business.
At the master’s level, you will start seeing programs that are specifically geared towards data science. They either specifically call out their association with data science or use related terms such as “machine learning”, “data mining”, or “business intelligence.”
This is particularly important if you are going for a business degree, as other programs are unlikely to provide the scientific or statistical rigor that is needed to become a successful data scientist. All these positions require a strong grasp on statistics, programing, and mathematics.
Key Positions Include:
Statistician: Statisticians use advanced statistical skills to design experiments and surveys that identify solutions to the challenges that their organization needs to address. Statisticians generally come from the more statistically rigorous programs and rely on statistical skills far more than programming or predictive algorithms.
Data Engineer: Data Engineers are responsible for extracting, importing, storing, and analyzing large and intricate data sets. Their primary responsibility is to ensure that an organization’s data is clean and complete from the data warehouse, all the way to its end users. Data engineers require very strong programming and database skills.
Machine Learning Engineer: Machine Learning Engineers analyze raw data, gathering information through data mining, and applying predictive algorithms and models to build tools and analysis useful for advancing business strategies. Machine Learning Engineers can be individuals who either have a statistical or programming background, but it is best to be equally strong in both.
Data Scientist: Data Scientists use computer science and statistics to solve complex computational problems and build infrastructure. The skills of this position frequently overlap with those of a statistician, data engineer, and machine learning engineer. However, they leverage an individual’s more advanced education to develop new methods, rather than rely on those that were built previously. Frequently deals with large quantities of unstructured data.