Alexander Kyng

To get certified this candidate had to display that they have the knowledge, skills, and abilities to perform a Data Scientist role. These included but were not limited to: - Data Management - Exploratory Analysis - Statistical Experimentation - Model Development - Coding for Production Environments - Communication and Reporting Through a series of questions on a range of topics, we are able to establish that this individual has the basic knowledge required for a data scientist role. We make use of adaptive testing approaches to understand to a high degree of confidence the skill level of individuals who take the assessments. Practical exam submission The final stage of the certification required the individual to complete a practical exam. This stage of the certification is graded manually and stringently by our data scientist experts. The practical exam is split into two parts: 1. Technical report: In the case of the technical report, the audience is a data science manager. It can be considered that the work is being presented to show how the task has been approached, why certain actions were taken, and how the work helps to solve the problem defined. There is no one right answer. 2. Non-technical presentation The final stage was to adapt the information towards a non-technical audience. It is a common requirement for data scientists to have to present their work to others who have no background in data science. These audiences are interested in why the work was done and what the outcome was, typically not how it was done.