TERMS OF REFERENCE (TOR) FOR STATISTICIAN / DATA ANALYST

Key Responsibilities

The Statistician / Data Analyst will be responsible for the following tasks:

1.     Develop statistical analysis plans (SAPs) in line with the study design or monitoring framework.

2.     Clean, process, and manage large datasets (#s of respondents, multiple waves, etc.).

3. Apply appropriate statistical methods (e.g., descriptive statistics, inferential statistics, regression modelling, multivariate analysis) to answer programme/research questions.

4.     Use statistical software packages (e.g., R, STATA, SPSS, Python) to conduct analysis, create reproducible code, and ensure transparency.

5.     Generate data visualisations (dashboards, charts, tables) and summary results to present to stakeholders.

6.     Interpret and communicate statistical findings clearly in written reports and presentations.

7.     Collaborate with the data collection and data management teams to ensure data integrity and quality assurance.

8.     Guide sampling methodology, weighting, and representativeness.

9.   Support the monitoring, evaluation, and learning (MEL) agenda through providing analytical expertise, contributing to learning briefs, and supporting decision-making.

  Ensure that all statistical outputs meet accepted standards, including documentation of code, methods, and assumptions.

Required Qualifications and Experience

1.     Master’s degree (MSc or equivalent) in Statistics, Biostatistics, Data Science, Mathematics, Economics (with heavy quantitative work), or a relevant analytical field.

2.     At least 5 years of professional experience in quantitative data analysis within research institutions, non-governmental organisations, consulting firms, or equivalent.

3.     Demonstrated proficiency in the use of statistical software packages (R, STATA, SPSS, Python) and data visualisation tools (Power BI, Tableau, etc).

4.     Proven track record of designing and analysing surveys, research studies, or monitoring & evaluation programmes and producing actionable insights.

5.     Strong analytical thinking, attention to detail, and ability to translate complex quantitative results into clear messages for non-technical stakeholders.

6.     Excellent written and verbal communication skills in English.

7.     Ability to work collaboratively as part of a multidisciplinary team and operate under deadlines in Abuja.

Desirable:

1.     Experience working in Nigeria or West Africa, with an understanding of local data contexts and challenges.

2.     Experience with sampling, weighting, and handling large-scale datasets.

3.     Experience with machine learning / predictive modelling, though not essential.

4.     Experience in dashboard development and interactive data visualisation.

5.     Familiarity with open-source software and reproducible analytical workflows.