As technology and the availability of business data expands, the employment outlook for data science professionals is only growing. According to a recent article in the Harvard Business Review, a shortage of data scientists is becoming a serious problem in some industry sectors.
IBM agrees with this assessment. The company predicts between now and 2020 that demand for data scientists and engineers will grow by nearly 40%. This trend is already playing out as we see many more data science and analysis positions being posted online. CEB TalentNeuron reports there were only 2,000 data science jobs posted in March 2014, but there were more than 10,000 in February 2016.
Data science and analyst jobs are growing in every sector, and you can certainly find a good employment opportunity with a data scientist and analyst degree. Some of the best job opportunities include:
#1 Data Scientist
A data scientist is in charge of discovering new insights from large amounts of unstructured and structured data that helps to meet or shape certain business needs or goals. The data scientist job is becoming more important today; businesses are relying more heavily on data analytics to make good business decisions and to lean on machine learning and automation are major parts of corporate IT strategies.
The major objective of a data scientist is to both organize and analyze massive amounts of data that many companies can now produce with advanced computer systems. Scientists use specialized software that is designed for this task. The results of the data scientist’s analysis must be easy enough to understand that all stakeholders can grasp it. This is especially important for people who do not work in information technology.
The approach of a data scientist to his data analysis will depend upon the industry and the needs of the company or department they are employed by. Before the data scientist can discover meaning in unstructured or structured data, business leaders and managers need to communicate what they are looking for.
Thus, a data scientist needs to have sufficient expertise in the business to be able to translate business goals into deliverables that are based upon data, such as pattern detection analysis, optimization algorithms and prediction engines.
#2 Data Analyst
The data analyst is responsible for data analysis for highly complex sets and systems of data, as well as documenting data flow, data elements, dependencies and relationships in an organization. Also, they are responsible for developing reusable and automated routines to extract requested information from databases.
Data analysts are responsible for tracking many types of business data and creating visual graphics and business presentations to present to senior stakeholders in organizations in all industries. Data analysts might be responsible for extracting data that are related to shopping trends and consider the fact that shopping behavior can depend upon demographics, seasons and gender. A data analyst would present their findings through using various visual graphic tools.
Data analysts should be skilled with Microsoft SQL server, Oracle and IBM DB2. The database analyst role is somewhat similar to that of business intelligence analyst, but the data analyst does not usually have a role in making decisions for the company.
#3 Data Mining Engineer
A data mining engineer is a professional who has highly specialized skills to create software solutions focused on big data. Data mining engineers collect massive amounts of organization data, which sometimes will be unstructured information. You also may be responsible for maintaining and building software infrastructure in a company to handle the massive amounts of data coming in from various sources. Data mining engineers use many advanced programming and scripting languages to initiate and develop these big data solutions.
Data engineers always have a heavy programming background, which is usually in Java, Scala and/or Python. They also have a strong stress upon distributed systems and big datas. Data engineers need to have both advanced and system creation skills to be successful.
While there is some overlap between a data scientist and data mining engineer, the latter has a higher level of programming skills than a data scientist. A data scientist creating a data pipeline is a highly advanced skill, but it is quite common for the data engineer. This is a task that requires a high level of programming skill, an understanding of big data frameworks, and system creation.
As a statistician, you will be responsible for extracting many types of data from various databases with many statistical methods and tests. You also need to be sure of the validity and quality of the conclusions after you have collected all of this information. It is then presented to senior managers for them to make business decisions. Statisticians also need to have excellent communication skills so they can relay important business information to non-technical managers and staff.
#5 Business Intelligence Manager
A business intelligence manager performs market research and makes various reports from large amounts of structured data. Business intelligence managers and specialists frequently use SQL, statistical tools and machine language to write reports and analysis, then send these work products to senior managers to make critical business decisions.
#6 Project Manager
Your primary role will be to affect and influence major business decisions after you use and evaluate data and insights that are provided by the major departments of an organization. Project managers deal with massive amounts of data, planning, and making sure the project work meets the necessary standards and per the established budget. Many companies will require you to have an advanced knowledge of statistics.
Earning a data scientist and analyst degree will make you qualified for many advanced data careers. Which one is for you depends upon the type of career that you want to have.
- Data Science Careers Outlook. (2016). Retrieved from https://datasciencedegree.wisconsin.edu/data-science/data-science-careers/
- What Is a Data Scientist? (2017). Retrieved from https://www.cio.com/article/3217026/data-science/what-is-a-data-scientist-a-key-data-analytics-role-and-a-lucrative-career.html
- Why It’s a Great Time to Be a Data Analyst. (2016). Retrieved from https://www.roberthalf.com/blog/salaries-and-skills/why-its-a-great-time-to-be-a-data-analyst