Moove is on a mission to make Africa and other emerging markets more productive and successful by redefining access to auto finance and vehicle ownership. Our starting point is a technology-enabled lending model to radically transform the availability of auto finance and vehicles for on-demand ridesharing services across tier 1 African cities. By doing so, Moove is creating sustainable jobs for mobility entrepreneurs in the mobility sector.
About the Role
- As a Data Analyst for Reconciliation & Payments, you will support Moove’s operations by performing data analysis, ensuring data quality, and providing business insights.
- Your role will involve conducting exploratory analysis, automating recurring data requests, and supporting business and product strategies with actionable insights.
Responsibilities
What You’ll be Doing:
- Develop and maintain cross browser compatible web and mobile based applications and work closely with team to enhance existing functionalities
- Take charge and be a decision driver for assigned web platforms
- Ability to explain issues, decisions and solutions to the team succinctly
- Produce prototypes and effectively articulate design decisions
- Keep up-to-date on emerging technology solutions, particularly those on JavaScript, for continuous improvements in front-end application development and end-user experience
- Open to work in Low-code No-code tools and Backend
Who You'll Be Working with:
- Directly reporting to our Lead Data Analyst , and closely working with our Product, Data and Engineering Teams.
Requirements
What You will need for this position:
- Degree in Mathematics, Economics, Computer Science, Information Management, Statistics.
- Advanced SQL proficiency (cohort analysis, complex joins, window functions, etc.).
- Experience with Python for exploratory data analysis and automation
- Knowledge of reporting tools like Looker/Holistics/Quicksight.
- Experience: Proven experience in data analysis, working with business users to create reports and dashboards, and delivering actionable insights. Familiarity with statistical packages (e.g., Google Sheets, Python libraries).
- Skills: Strong problem-solving abilities, attention to detail, critical thinking, and business acumen.
- Ability to communicate insights clearly & collaborate with cross-functional teams.
Method of Application
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