Overview

Sightsavers is looking for a motivated and skilled Monitoring, Evaluation, and Learning (MEL) professional to join the dynamic, global MEL team as the MEL Advisor (Data Analysis). The post holder will provide MEL support to a portfolio primarily comprised of inclusive economic empowerment (EE) projects implemented globally.  Economic empowerment is a relatively new and rapidly expanding thematic area for Sightsavers and the post holder will be responsible for analysing the data to support learning, adaptive management and reporting.

Responsibilities

The MEL Advisor (Data Analysis) will collect, analyse, and interpret data to support decision-making, optimise data collection tools, and ensure data integrity. This role involves managing databases, conducting data quality assessments, developing protocols, and supporting learning initiatives. The ideal candidate will have strong analytical skills, experience in data visualisation, and the ability to collaborate across teams.

The post holder is expected to travel up to eight weeks a year.

Principal accountabilities:  

Data management and analysis

Update programme dashboards quarterly, ensuring they remain accurate and reflective of metrics. Refine and adapt these dashboards to enhance usability and relevance, aligning them with evolving programme and MEL needs and insights.

Conduct analysis of employment data and economic empowerment databases.

Maintain economic empowerment databases, ensuring continuous functionality and robust data security.

Conduct qualitative analysis (content analysis) of learning logs from economic empowerment programmes.

Track, review, and analyse completion of learning reports and logs from COs to identify trends and areas for improvement.

Conduct analysis of survey data from education, health and economic empowerment programmes.

Explore innovative approaches to enhance efficiency and improve outcomes by assessing and refining analytical techniques of MEL data

Data quality and privacy

Support COs in identifying and addressing quality gaps in their economic empowerment databases and learning logs to ensure accuracy and completeness of project data.

Develop and implement Data Quality Assurance protocols, including data cleaning procedures for COs on the databases and reported data.

Conduct Data Quality Assessments (DQA) and contribute to DQA protocol development.

Develop data flow mapping and Data Protection Impact Assessments (DPIAs).

Outcome level data collection

Design and develop data collection tools to streamline data gathering processes mainly within the economic empowerment portfolio.

Develop data collection, analysis and management protocols.

Optimise existing data collection systems for efficiency and accuracy.

Collaborate with stakeholders to ensure tools meet programme and organisational needs.

Implement automation techniques to improve data processing workflows.

Provide training, technical support and troubleshooting for data collection tools.

Reporting and data visualisation

Create compelling visualisations to effectively communicate data insights for internal stakeholders (e.g. EE technical team, EE Community of Practice) and external stakeholders (e.g. project steering committees).

Compile reports based on their data analysis, and present findings in clear and actionable manner to support decision-making and adaptative management.

Support programme and donor reporting, ensuring the accuracy and integrity of the reported data, validating sources and implementing quality control measures to maintain reliability.

Consolidate analysis of the learning logs, providing insights on the implementation of the learning framework.

Participate in meetings and workshops to present findings or to represent the MEL team as needed.

Skills and Experience

We are looking for an individual with excellent critical thinking skills and the ability to work independently. You will be solutions-focused and ideally able to leverage AI tools.

Knowledge (education and related experience):  

Essential

Bachelor's degree in Data Science, Statistics, Business Analytics, or a related field.

Experience in database management and data visualisation.

Proven track record of successfully applying data analysis/statistical techniques to datasets within health, education, economic empowerment, international development or other fields directly related to Sightsavers’ thematic portfolio.

Practical experience of good data quality and data cleaning practices to prepare data sets for use in analytics software and data quality assessment methodologies and reporting techniques.

Experience of data flow mapping and data privacy methods.

Experience of capacity building and supporting staff in different contexts (face to face, online) to deliver data collection to deadlines.

Understanding of international development issues and a commitment to promoting equality of opportunity for marginalised groups including people with disabilities.

Desirable

Master’s degree in international development, international relations, geography, statistics or appropriate equivalent.

Experience in cross-country and functional teams.

Experience in supporting learning initiatives e.g. adaptive management or Collaborate, Learn and Adapt (CLA) methodology.

Familiarity with AI supported tools for data processing.

Practical experience of DHIS2 for data collection, reporting and visualisation.

Experience using the Washington Group questions on disability

Skills (special training or competence):  

Essential

Strong proficiency in data analysis tools (Excel).

Proficient in the use of Power BI, Tableau or other data visualisation software.

Familiarity with automation techniques such as Power Query for data processing.

Good analytical skills with the ability to identify important issues and communicate these effectively to a non-technical audience.

Able to work with multiple stakeholders and ensure differing concerns and priorities are effectively managed.

Fluent in English, with experience of writing reports and briefings in English.

Demonstrated ability to effectively prioritise work with competing deadlines.

Able to travel for up to eight weeks per year.

Desirable

Experience of digital transformation, implementing new software/tools/working practices within an organisation.

Experience in other data analysis tools e.g. Stata, SQL, Python, R.

French, Swahili and/or Portuguese language skills.

Previous overseas experience i.e. either professional or voluntary work.

  Core behaviours: 

A great team player and highly collaborative.

Excellent organisation, self-motivation and independent working.

Methodical, analytical, and accurate.

Solutions-focused, flexible and patient.

Able to give and receive constructive feedback.

Assertive and willing to take difficult decisions and see them through.