Session Description: As ecological researchers, we acquire a suite of skills that are highly transferable. Understanding how to deal with the noisy and complex data is commonplace in ecological research, for instance. Ecologists are also skillful in data management, complex analytics, and diverse methods to extract actionable insights and answer scientific research questions. All of these skills are also essential for data science. For individuals looking for a career outside of academia, data science can satisfy an interest in answering complex, interesting research objectives such as understanding consumer insights, detecting fraud, ensuring cyber security, or designing video games. There are also opportunities for potential gains in work-life balance and compensation. However, translating an ecologist’s experiences into relevant skills for a data science position requires some understanding of both disciplines. In this workshop, we use our experiences as data science-curious ecologists (who are presently in academia) to discuss important considerations for those contemplating a career shift from academic ecology to industrial data science. We will discuss ways in which programming languages and key tools are shared between disciplines as well as skills that are relatively industry-specific. This workshop will also include interactive activities such as a short introduction to SQL and a Q&A with former ecologists who are now in data science.
