Senior Data Analyst - Statistics and Market Research

Role overview

Key responsibilities

• Contribute to and guide research design, questionnaire development, sampling plans, and sample size calculations.
• Analyse market research, customer experience, satisfaction, opinion poll, and panel-based survey data.
• Clean, validate, and prepare datasets, checking missing values, inconsistent responses, outliers, and duplicate records.
• Assess panel response quality, including speeding, straight-lining, eligibility, and potential survey fraud.
• Develop and apply weighting approaches, assess representativeness, and explain sampling limitations and potential bias.
• Prepare cross-tabulations, significance tests, and subgroup comparisons; apply regression, segmentation, factor analysis, and driver analysis where suitable.
• Analyse repeated survey waves, tracking studies, and panel trends.
• Produce charts, dashboards, analytical reports, and client presentations.
• Work with research and fieldwork teams to monitor quotas, resolve data issues, and maintain analytical accuracy.

Required qualifications and experience

• Bachelor’s or master’s degree in statistics, applied statistics, mathematics, econometrics, or a related quantitative discipline.
• At least 3 years of hands-on experience analysing market research and panel-based survey data.
• Strong understanding of sampling, weighting, hypothesis testing, confidence intervals, and multivariate analysis.
• Proficiency in SPSS and/or R or Python for statistical analysis.
• Strong Excel skills and experience with survey datasets and respondent-level data.
• Ability to distinguish statistical significance from practical business relevance.
• Strong written communication and ability to explain findings to non-technical audiences.

Preferred qualifications

• Experience with online research panels, longitudinal studies, and multi-country surveys is preferred.
• Knowledge of SQL and visualisation tools such as Power BI or Tableau is preferred.
• Familiarity with research quality standards and ethical handling of respondent data is preferred.