Data Analyst, Reconciliation & Payments at Moove

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.