experimental economics, data science & visual analytics
Getting access to information and accumulating large data sets (about individual characteristics, preferences, habits and emotions) is key to many questions and challenges of our times. However, data becomes valuable if and only if we are able to use it, for instance to make better decisions by taking into account the collected information or identified patterns. Collecting data gets even more interesting when we are able to build engines that help to make predictions, e.g. upon individual preferences or behavior. Building - so called - data products that allow to identify hidden patterns or developments, make predictions or decision recommendations not only requires software developing skills, but domain knowledge, analytics and many times a deep understand of (analyzing and influencing) human decision making, as well.
As a data scientist with a broad background in the social sciences - especially in differential psychology and experimental economics, and experienced consultant, I help organizations
- to develop a data strategy
- to focus in the right questions when starting to collect data
- to develop experimental designs for collecting and analyzing data
- to prepare and analyze structured and unstructered information
- to visualize data and analytics in static reports or dynamic dashboards
- to develop scores and algorithm to foster (automized) data-driven decision making
Usually I base those data products on the following languages and frameworks.
Moreover I use commercial solutions like