Some common training for a career as a data scientist includes an understanding of mathematics, statistics and computer programming, as well as a foundation in business practices and concepts. This typically results from a combination of courses at a college or university along with practical work experience at various types of companies.
Though the field of data science is relatively new compared to other branches of science, it carries a consistent set of training requirements across positions and employers, beginning with a focus on mathematical concepts. The basic tasks of a data scientist involve analyzing large amounts of data, typically gathered from a business through either directly surveying customers or by tracking customer usage patterns across a product or service. Thus, the data scientists needs a strong understanding of statistics and similar analytical operations to take the date, segment it accordingly, and turn it into graphs, charts or number sets for interpretation.
The second major aspect of a career in data science is the ability to also analyze the information and make suggestions for how the business should proceed in various situations. For example, a data scientist may look at the demographics of a company's user base to determine factors such as the gender, income levels and usage patterns of its highest-paying customers. The scientist is then able to make recommendations on how to attract more customers in a similar demographic or convert customers in different demographics.