Back ground
Bodmando’s Evaluation Unit is seeking a competent and detail-oriented Quantitative Data Analyst to strengthen its research and evaluation team. The successful candidate will support quantitative research design, data management, statistical analysis, interpretation and presentation of findings across multiple consultancy assignments..

Duties and Responsibilities

The Quantitative Data Analyst will:

Support the design of quantitative research methodologies, sampling approaches and survey instruments.
Develop and program quantitative data collection tools using platforms such as KoboToolbox, ODK, SurveyCTO or similar systems.
Develop sampling frameworks and support calculation of appropriate sample sizes.
Monitor incoming survey data and undertake routine data quality checks during fieldwork.
Clean, code, validate, merge and manage quantitative datasets.
Conduct descriptive and inferential statistical analysis using SPSS, Stata, R, Python or similar statistical software.
Produce frequencies, cross-tabulations, means, proportions, confidence intervals and other relevant statistical outputs.
Undertake disaggregated analysis by variables such as sex, age, location and other relevant characteristics.
Support more advanced analysis, including regression and statistical testing, where required.
Interpret quantitative findings and translate statistical outputs into clear findings for evaluation and research reports.
Develop high-quality tables, graphs, charts and data visualisations.
Support triangulation of quantitative findings with qualitative and secondary data.
Contribute to baseline, endline, evaluation, assessment and research reports.
Maintain organised and secure project datasets, syntax files, codebooks and analysis outputs.
Support quality assurance of data collected by field teams.
Undertake other data analysis and research-related responsibilities assigned by the Team Lead or Programmes Manager.
Qualifications

Bachelor’s degree in Statistics, Economics, Quantitative Economics, Mathematics, Data Science, Monitoring and Evaluation, Public Health, Social Sciences with strong quantitative training, or a closely related field.
A postgraduate qualification in a relevant field will be an added advantage.
At least 2–3 years of demonstrated experience in quantitative data management and statistical analysis.
Strong practical competence in at least one statistical package, preferably SPSS, Stata, R or Python.
Experience using electronic data collection platforms such as KoboToolbox, ODK or SurveyCTO.
Demonstrated experience analysing survey, evaluation or research datasets.
Good knowledge of quantitative research methods, sampling and statistical analysis.
Strong Microsoft Excel skills.
Ability to develop clear tables, graphs, dashboards and other visual presentations of data.

Required Competencies

Strong analytical and numerical skills.
Excellent attention to detail and commitment to data accuracy.
Ability to identify inconsistencies and data quality problems.
Ability to interpret statistical results and communicate them in simple, meaningful language.
Good report-writing and presentation skills.
Ability to work on multiple assignments and meet tight consultancy deadlines.
Ability to work independently while collaborating effectively with multidisciplinary and international teams.
High standards of confidentiality, research ethics and responsible data management.
Strong written and spoken English.

Interested candidates must submit all four (4) items listed below. Failure to submit any of the required items will result in automatic disqualification.

An updated CV;
A brief cover letter outlining relevant quantitative data analysis experience;
Minimum of 2 relevant work samples demonstrating quantitative data analysis skills, such as anonymised analytical reports, statistical outputs, dashboards, data visualisations or similar products; and
Expected monthly remuneration.
The email for submission of applications