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.
What You’ll be Doing
- Conduct exploratory data analysis using statistical techniques to identify patterns, trends, anomalies, and insights.
- Work closely with business and product teams to prioritise data needs and support decision-making.
- Perform impact and gap analysis, recommending improvements based on product and business requirements.
- Create data visualisations & reports to effectively communicate findings to stakeholders.
- Collaborate with Data Engineering to automate insights for recurring data requests.
- Collaborate with Operations for timely and accurate data inputs for Reconciliation.
- Act as a gatekeeper for data quality, ensuring accuracy and consistency across individual and merged datasets.
- Handle ad-hoc requests for data discovery and analysis to support business objectives.
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.
Who You'll Be Working with:
- Directly reporting to our Lead Data Analyst, and closely working with our Product, Data and Engineering Teams.
Method of Application
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