Junior Data Analyst

The Junior Data Analyst, part of the Analytics team within the Venn department, is responsible for managing the data lifecycle from collection and storage to cleaning, analysis, reporting, and innovation while also facilitating learning and information exchange across teams.

This entry-level role is ideal for someone with strong analytical skills, a passion for data, and a willingness to learn and grow in the field of analytics.

• Analyze and interpret program data (input, output, and outcome data) to support decision-making.

• Responsible for sorting, cleaning, validating, and aggregating raw data files for analysis.

• Support in conducting data quality checks, control, and management for field collection activities.

• Responsible for organizing and storing data outputs, ensuring that all reports derived from analyzed data are accurately completed, properly documented, and saved in the appropriate folders for future reference and use.

• Collaborate with the other Venn team units to design appropriate data collection and aggregation tools, with plans to routinely update them for data quality improvement.

• Support the management of the organization’s Centralized M&E Database with automated workflows for real-time information and data visualization.

• Support in the planning and coordinating of field surveys, including the development of work plans, schedules, and other necessary guiding tools like survey guidelines related to safeguarding the confidentiality, integrity, and quality of data collected.

• Build capacity for field staff to achieve their data collection targets and present data and information in the best possible format for further analysis.

• Support in the completion and compilation of project monitoring and evaluation reports for decision-making.

• Other duties as required by supervisors.

• Proven working experience for at least one year conducting data analysis.

• University degree in Statistics, Economics, Quantitative Economics, Mathematics, or any related field.

• Must have statistical analysis experience using STATA; R/Python programming is an added advantage.

• Strong analytical skills with the ability to organize, analyze, and disseminate significant amounts of analysis findings with attention to detail and accuracy.

• Demonstrated knowledge and understanding of the application of Theories of Change (TOC).

• Ability to apply M&E process-based tools, including result-based and participatory monitoring and evaluation, feasibility studies, data quality assurance, and reporting.

• Strong training & facilitation skills.

• Team player, yet self-motivated and proactive.

• Flexibility to work effectively with changing priorities and competing deadlines.

• Experience in participatory research within last-mile communities will be an advantage.