Data science connects math and statistics, programming, analytics, machine learning and artificial intelligence to analyze and understand an organization’s data. Businesses can use these insights to make decisions and plan strategically. More and more organizations are seeing the benefit of using analytical data to improve business performance, creating more job opportunities in data science. There are many different occupations in this growing field, including data analyst, data architect, data engineer and business analyst.
Online master’s degree
Kettering University Online offers an online master’s in data science which teaches students the theories and practical applications of database management and analytics. As well as the core modules, students can choose specializations to customize the program to their interests and career goals.
What qualifications do you need?
Many people working in data science have a bachelor’s degree in computer science, math, data science, economics, engineering or statistics. Some have a master’s or a doctorate in big data, business analytics, data analytics or data science. Graduates with other degrees can take a master’s conversion course in data science.
Some large employers offer graduate training schemes, and it is also possible to enter this profession through an apprenticeship degree scheme.
Another route could be getting a data entry job and working your way up to a data scientist position. You could do workplace qualifications and self-directed online learning. It can help to have certificates for specific tools and skills, such as machine learning.
It is good to have experience in programming software packages like R, SQL, SAS, Java and Python. Learning about data visualization tools such as Tableau, Power BI and Excel is also helpful.
Coding boot camps can give you valuable knowledge and experience, and there are also some free coding courses.
Several larger employers offer internships, which can help you understand the workplace and the reality of working in data science. You could also approach smaller organizations for intern or shadowing opportunities.
Competitions and events
There are online science competitions run by organizations like Kaggle and Topcoder, and employers keep an eye on these to find new, talented people.
Attend conferences and events to further your knowledge, meet others with similar interests and network with employers.
The leading employers tend to be in:
Universities and research institutions
Organizations in the above areas are keen to use data to understand their customers so that they can target relevant products and services.
When being interviewed for a data science job, you may be asked technical and behavioral questions. You can prepare by practicing by saying your answers aloud and preparing examples from work or university that demonstrate your knowledge and skills.
Here are some example questions:
What are the advantages and disadvantages of a linear model?
What is the ROC curve?
What is a confusion matrix?
What are recommender systems?
How do you build a random forest model?