An article published by Forbes in 2017, revealed some of IBM’s latest predictions. According to the article, careers that require the use of machine learning skills have a median annual salary of $114,000. Data scientists working with these skills have an average salary of $105,000 a year, while data engineers make about $117,000. It was also pointed out that nearly 60 percent of data science jobs are found in one of three fields: IT, finance and insurance, or professional services. The average length of time that a data science job opening stays on the workforce market is 45 days, meaning employers don’t just pick the first person that applies. They leave their positions open for an extended period of time to make sure they can connect with top-talent candidates.
If you’re wanting to establish a career with a degree in data science, you’ll have plenty of openings to choose from. In fact, by the year 2020, there will be 700,000 new job positions that need to be filled. For now, here is a look at the different jobs you can get with your data science credential.
Careers for Data Science Graduates
Most people working in data science possess a master’s degree, making competition in the workforce somewhat competitive. If you don’t have a master’s, you’re going to find it difficult to secure anything more than an entry-level position. This multidisciplinary field requires you to master a wide range of skills, including those related to:
- Data analysis
- Data warehousing
- Database management
- Data processing
- Data retrieval
- End-to-end development
Business Intelligence Reporter
Consulting and reporting companies are among the top employers of data scientists. As a business intelligence reporter, you will spend your time analyzing various forms of market research and putting your findings into a structured set of data. You’ll use a wide range of tools to perform your tasks, including:
- Machine learning
- Statistical tools
- Report creation apps
Once you have created reports outlining your findings, you will send the reports to management and you may be asked to carry out presentations relating to how you believe the information should proactively be used to enhance your employer’s operational processes.
You will find employment as a project manager in all industries. Your responsibilities as a project manager will greatly vary and be based on the size of the company you are working for. The smaller the company, the smaller the projects. With your skill set as a data scientist, though, you will have the capability to land employment through large companies. In this role, you will be responsible for project ideas, project development, project execution, and project follow-ups. It is not uncommon for project managers to use their statistical skills throughout the completion of their tasks. The main goal of a project manager is to ensure objectives are met in the most efficient and effective manner possible.
Data analysts can often find employment in finance and manufacturing industries. Much of the tasks performed by data analysts are similar to those performed by business intelligence analysts, but data analysts tend to have more responsibilities associated with visual graphics. For example, data analysts often analyze data to find hidden insights and then they put this information into a visual format using a variety of visual graphics tools. Some of these visual analytics tools that data analysts use include:
- Dundas BI
- SAP Business Obejcts
Machine Learning Engineer
For many companies, the data that they analyze is the actual product that they sell. To produce these products, there is a lot of intense machine learning that takes place. Those who want to be employed by these companies will need to have advanced skills as a machine learning engineering. To excel in this line of work, you will need a formal educational background in any of the following fields:
As a data architect, you will spend your time building complex databases for your employer. Some of these databases will be for use by the public while others will store confidential information relating to customer information and business policies and protocols. Data architects often work on teams with other data science professionals, so effective collaboration and communication skills are a must. In addition to creating databases, you will be responsible for developing database blueprints, testing the databases, and performing database maintenance tasks.
Director of Global Intelligence
The director of global intelligence position is one that comes with great responsibility. You will need a master’s degree to secure this type of position, with some employers mandating a Ph.D. In this role, you will perform complex functions, including those related to:
- Collect competitive information through a variety of sources, including internal databases, CI vendors, etc.
- Management competitive intelligence
- Create reports and communicate with vendors as well as stakeholders
- Develops methods for strategic decision making
- Facilitate competitive simulations that outline the expectations of short- and long-term branding strategies
- Develop competitive landscapes
- Perform maintenance on competitive landscapes
In addition to a master’s or Ph.D., you will need an extensive amount of experience in market research to become the director of global intelligence. Pertinent qualities you will need to excel in as this type of director include:
- Interpersonal skills
- Analytical skills
- Organizational skills
- Communication skills
- Decision-making skills
Data miners spend their time putting raw data into a structured format and then analyzing (mining) the data to obtain meaningful information. This information is then used by the employer to improve their operational processes. Data mining is especially advantageous in a variety of fields, including:
- Governmental sectors
If you choose to become a Hadoop engineer, you will spend your time performing coding for Hadoop applications. In many ways, a Hadoop engineer is like a software developer. There are many responsibilities that a Hadoop engineer performs, but the exact duties depend on the domain and sector the engineer is working in. Generally, though, Hadoop engineers perform the following tasks:
- Use Hive and Pig for pre-processing activities
- Use disparate data sets to load data
- Development of Hadoop
- Implementation of Hadoop
- High-speed querying
- Translate complex functions and configurations into visual designs
- Management of HBase
- Deployment of HBase
- Propose best practices
Data scientists have skills that are in high demand. To be successful as this type of scientist, you will want to master the following tools:
- Apache Hadoop
- Machine learning
- Apache Pig
- Apache Hive
Even though data scientists are in such high demand, they are also extremely difficult to recruit. Those who have expert knowledge as a data scientist generally expect a hefty salary, and for many small businesses, meeting these salary demands simply isn’t feasible. To help you land a position with a large company, you will not only need to earn a degree but you will want to distinguish yourself in the workforce by earning a variety of certifications.