A data scientist combines computer science skills, statistics expertise, and the knowledge of their specific domain. Data scientists follow a more easily understandable processing approach as compared to statisticians. Data scientists have more coding knowledge than statisticians and more statistics knowledge than software engineers.

Data scientists focus on reading in data and transforming it, building models to understand data, and analyzing that data. Data scientists can take on a lot more data because they are skilled in organizing and transforming it. After sorting the data they look for valuable insights. In order for them to analyze their data and draw conclusions, they create many different models through machine learning and compare them to see which is the most accurate.

Data scientists and statisticians are similar because they both take collected data and analyze it to obtain knowledge and understanding of specific topics. While their end goals are similar their processes, as well as the type of data, used differ. Statisticians normally focus on a singular model whereas data scientists develop multiple models to analyze their data. Data scientists can handle a more vast amount of data whereas statisticians can only focus on a smaller amount. They also study different types of problems and use different terminology and processes to find solutions. Data scientists also have more background in areas such as computer science whereas statisticians have a much deeper understanding of statistics.

I view myself as more of a data scientist. I have a lot more background in computer science and information technology than I do statistics with my major being Information technology. Through the Applied statistics and data management certificate I have gained significant knowledge in statistics that has allowed me to apply my statistics knowledge to my computer programming.