Independent Trainer-Statistical Literacy

About the RoleWe are currently looking for a senior freelance trainer and practitioner specializing in statistical literacy, the social interpretation of data, cognitive bias, and evidence-based decision-making. The trainer should help professionals critically evaluate statistics, understand how context shapes conclusions, and communicate findings responsibly.ResponsibilitiesHelp professionals critically evaluate statistics.Help professionals understand how context shapes conclusions.Help professionals communicate findings responsibly.Deliver interactive training to professionals, managers, analysts, and senior specialists.Adapt examples to ADEK’s education and regulatory context (for UAE/GCC delivery).Facilitate discussion of privacy, transparency, responsible interpretation, and ethical communication.Guide participants in weighing conflicting evidence, challenging assumptions, and presenting balanced recommendations.QualificationsMaster’s degree or PhD in Sociology, Social Statistics, Applied Statistics, Behavioural Science, Public Policy, Social Research, or a closely related discipline.Demonstrated expertise spanning quantitative research methods and the social or behavioural dimensions of data interpretation.A recognised adult-learning or facilitation qualification would be an advantage.Required SkillsIdeally 8–10 years of relevant experience in applied research, data interpretation, policy analysis, behavioural insights, or organisational decision support.At least 5 years of experience delivering interactive training to professionals, managers, analysts, and senior specialists.Experience working with government entities, education authorities, or public-sector research organisations.UAE/GCC delivery experience is preferred, with the ability to adapt examples to ADEK’s education and regulatory context.Required Expertise:Sociology of data: Explain how institutional priorities, social context, definitions, classification choices, and stakeholder perspectives influence data collection and interpretation.Statistical literacy: Explain averages, distributions, percentages, rates, trends, sample size, uncertainty, and statistical significance in accessible language.Misleading statistics: Identify misleading averages, inappropriate comparisons, relative versus absolute changes, and unsupported conclusions.Bias and human judgment: Address selection, measurement, survivorship, confirmation, and algorithmic bias, alongside framing, anchoring, and availability effects.Correlation and causation: Help participants distinguish association from causation and recognise confounding variables and limitations in evidence.Research and surveys: Evaluate sampling approaches, survey design, response bias, margins of error, and the reliability of research findings.Charts and dashboards: Critically assess scales, visual framing, missing context, and misleading data presentation.Data ethics: Facilitate discussion of privacy, transparency, responsible interpretation, and ethical communication.Evidence-based decisions: Guide participants in weighing conflicting evidence, challenging assumptions, and presenting balanced recommendations.