JOB PURPOSE

The Programme Data Analyst will work closely with the M&E Manager for the SLL programme and the implementation team as well as supporting the SLL M&E country teams and implementing partners. The role of the analyst will be to collect, manage, quality assurance, analyze and interpret all programme related datasets. The insights gathered from the data will be used to support informed decision-making across the programme. The analyst will collaborate with the programme team to develop data-driven solutions and effectively communicate the findings to stakeholders. The ideal candidate should have strong analytical skills, proficiency in data manipulation and visualization techniques. Additionally, the candidate should be able to work independently as well as part of a team.

DUTIES AND RESPONSIBILITIES

Data collection and integration

• Collect, clean, and pre-process data from various sources, including databases, spreadsheets, APIs, and external datasets.
• Integrate data from disparate sources to create comprehensive datasets for analysis.

M&E Implementation

• Support project design activities including development of project theories of change and strategic frameworks (Results Frameworks, Log Frames etc.)
• Support AIMs and work with data platforms, databases and select technologies to capture and organize data
• Oversee and execute M&E activities included in the SLL programme Plans, with particular focus on results, impacts, best practices, lessons learned, emerging issues and setbacks in implementation

Data Analysis and Interpretation

• Perform descriptive and exploratory data analysis to identify patterns, trends, and correlations within the data.
• Apply statistical techniques and machine learning algorithms to extract meaningful insights and predictive models.
• Conduct hypothesis testing and sensitivity analysis to validate findings and assess uncertainty.

Dashboard Development and Visualization

• Design and develop interactive dashboards and reports to visualize key performance indicators (KPIs) and metrics.
• Utilize data visualization tools (e.g., Tableau, Power BI) to create compelling visualizations and story telling that facilitate understanding and decision making.

Data Quality Assurance

• Ensure data integrity and accuracy by implementing data validation checks and quality assurance processes.
• Identify and resolve data inconsistencies, outliers, and missing values to maintain data reliability.

Collaboration and Communication

• Collaborate with stakeholders across the unit/programme to understand business requirements and translate them into data analysis projects.
• Communicate analysis results and insights to non-technical audiences through clear and concise reports, presentations, and visualizations.
• Provide guidance and support to colleagues on data-related issues and best practices.

Continuous Improvement

• Stay informed about advancements in data analytics techniques, tools, and technologies.
• Identify opportunities for process improvement and optimization through data-driven approaches.
• Actively contribute to the development of data analytics strategies and initiatives to drive organizational growth and innovation

REQUIREMENTS

Education and Experience

• Bachelor’s degree in Data Science, Information Management, Computer Science, Statistics,
• Development economics, Epidemiology or a related field
• Minimum five (05) years proven experience as a Data Analyst or similar role, with a strong track record of data analysis and interpretation.
• Multi-country experience is a requirement.
• Detailed knowledge of key M&E concepts, tools and best practices; experience working with both quantitative and qualitative data collection and analysis methodologies; familiarity with routine management of information systems.
• Experienced working with District Health Information Systems (DHIS) across different countries will be an added advantage
• Proficiency in programming languages such as Python, R, SQL, or similar for data manipulation and analysis.
• Experience with data visualization tools such as Tableau, Power BI, or similar

Knowledge, Skills and Competencies

• Knowledge of statistical techniques, machine learning algorithms, and data mining methodologies.
• Excellent analytical and problem-solving skills, with the ability to translate complex data into actionable insights
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross functional teams.
• Attention to detail and a commitment to maintaining data integrity and quality.
• Ability to manage data from multiple projects/countries simultaneously and meet deadlines in a fastpaced environment