Independent Trainer - Statistical Literacy

About the role

A senior freelance trainer and practitioner is sought to deliver training on statistical literacy, the social interpretation of data, cognitive bias and evidence-based decision-making. The trainer helps professionals critically evaluate statistics, understand how context shapes conclusions and communicate findings responsibly. The work is delivered interactively to professionals, managers, analysts and senior specialists, with examples adapted to the education and regulatory context of the UAE/GCC.

Key responsibilities

• Help professionals critically evaluate statistics and understand how context shapes conclusions.
• Deliver interactive training to professionals, managers, analysts and senior specialists.
• Adapt examples to the education and regulatory context of the UAE/GCC.
• Facilitate discussion of privacy, transparency, responsible interpretation and ethical communication.
• Guide participants in weighing conflicting evidence, challenging assumptions and presenting balanced recommendations.

Required profile

• Master's degree or PhD in Sociology, Social Statistics, Applied Statistics, Behavioural Science, Public Policy, Social Research or a closely related discipline.
• Demonstrated expertise in quantitative research methods and the social or behavioural dimensions of data interpretation.
• Ideally 8-10 years of experience in applied research, data interpretation, policy analysis, behavioural insights or organisational decision support.
• At least 5 years delivering interactive training to professionals, managers, analysts and senior specialists.
• Experience with government entities, education authorities or public-sector research organisations; UAE/GCC delivery experience preferred.
• A recognised adult-learning or facilitation qualification is an advantage.

Required skills

• Sociology of data: how institutional priorities, social context, definitions, classifications and stakeholder perspectives shape data collection and interpretation.
• Statistical literacy: explaining averages, distributions, percentages, rates, trends, sample size, uncertainty and statistical significance accessibly.
• Misleading statistics: spotting misleading averages, inappropriate comparisons, relative versus absolute changes and unsupported conclusions.
• Bias and human judgment: selection, measurement, survivorship, confirmation and algorithmic bias, plus framing, anchoring and availability effects.
• Correlation and causation: distinguishing association from causation and recognising confounding variables.
• Research and surveys: sampling approaches, survey design, response bias, margins of error and reliability of findings.
• Charts and dashboards: assessing scales, visual framing, missing context and misleading presentation.
• Data ethics and evidence-based decision-making.