- Job Title: Data Analyst, Reconciliation & Payments
- Location: Lagos
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About Moove
Moove is redefining what large-scale rideshare leasing and vehicle ownership look like in Africa. Through our innovative model, we are rapidly improving access to vehicles for on-demand ridesharing services in major metropolitan cities, while also creating sustainable employment opportunities for drivers.
About the Role
We are seeking a Data Analyst, Reconciliation & Payments to join our growing team. In this role, you will support operations by conducting data analysis, ensuring data quality, and generating business insights that drive decision-making. You will collaborate across product, engineering, and operations teams to ensure timely reconciliations, automate reporting, and provide actionable recommendations.
Key Responsibilities
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Conduct exploratory data analysis using statistical techniques to identify patterns, trends, anomalies, and insights.
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Partner with business and product teams to define and prioritize data needs.
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Perform impact and gap analysis to recommend improvements aligned with business and product requirements.
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Develop clear and effective data visualizations, reports, and dashboards for stakeholders.
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Collaborate with Data Engineering to automate recurring data requests and streamline insights delivery.
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Work with Operations to ensure timely and accurate inputs for reconciliation and payments processes.
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Serve as a gatekeeper for data quality, ensuring consistency and accuracy across datasets.
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Handle ad-hoc data discovery and analysis requests to support evolving business objectives.
Requirements
Education & Experience
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Degree in Mathematics, Economics, Computer Science, Information Management, Statistics, or related field.
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Proven experience in data analysis, reporting, and delivering actionable insights to business users.
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Hands-on experience with statistical analysis and packages (e.g., Python libraries, Google Sheets).
Technical Skills
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Advanced SQL proficiency (complex joins, cohort analysis, window functions, etc.).
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Experience with Python for exploratory data analysis and process automation.
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Familiarity with reporting tools (Looker, Holistics, Quicksight, or similar).
Soft Skills
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Strong problem-solving and critical-thinking skills.
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High attention to detail and accuracy.
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Ability to clearly communicate insights and recommendations.
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Business acumen with the ability to work collaboratively across teams.
Who You’ll Work With
You will report directly to the Lead Data Analyst, and work closely with Product, Data, Engineering, and Operations Teams.
