Data science is the study and application of data to inform decision-making, often in the belief that it can improve outcomes. While much attention is paid to artificial intelligence, sensors and computing, less attention is paid to the humans who work with the technologies – apart from a range of policies to increase the number of them. Yet, as Beer (2018) points out, the power of data is in the hands of those who can interpret it. Data is not neutral and outcomes depend on what data is being used, how it is gathered, who is making the decision, why they are making the decision, who the decision is being made about and who else may be affected, issues which lie at the core of big data and algorithmic culture debates (Kitchin, 2014; Kelleher and Tierney, 2018). As recent data scandals involving Facebook and Cambridge Analytica reveal, data science workers can create services which introduce new social and political inequalities with little to no recourse. Despite a visible increase in discourses about ethical frameworks, and the need for legal frameworks to protect data privacy in Europe, it is far from clear if these policy solutions are adequate to protect individual and collective rights from such behaviour.