Data Analyst, Reconciliation & Payments (Mexico City OR Bogota)

About Moove

Moove is on a mission to build the largest mobility fintech for emerging markets. 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 LatAm and USA 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. Working with colleagues in LatAm and across the globe, you must have proficiency in the Spanish and English languages.

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.

• 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.

What You will need for this position

• Degree in Mathematics, Economics, CompSci, Information Management, Statistics.

• Advanced SQL proficiency (cohort analysis, complex joins, window functions, etc.).

• Experience with Python or R for exploratory data analysis

• Knowledge of reporting tools like Looker/Holistics.

• 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 Operations Teams.

About the team

Our team is collaborative, positive, curious, and engaged. We think fast, work smart, laugh often, and are looking for like-minded people to join us in our mission to disrupt vehicle ownership and make financial freedom within reach.

Moove is strongly committed to diversity within its community. The Company’s approved Employment Equity Plan and Targets will be considered as part of the recruitment process. As an Equal Opportunities employer, we welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently.

Pre-hiring Notice: Moove relies on the accuracy of information contained in employment applications, as well as the accuracy of other data presented throughout the hiring process and during employment. Any misrepresentations, falsifications, or material omissions in any information or data provided by an applicant may result in the applicant being excluded from further consideration for employment or if an individual has already been hired, termination of employment.

EEO Statement: Moove is an equal opportunity employer and does not discriminate on the basis of gender, race, sexual orientation, marital status, religion, political affiliation or any other protected characteristic.

Moove: Moove is a mobility asset finance company and Uber's preferred fleet partner across Sub-Saharan Africa. Our Vision is to democratise financial services to make our customers more productive and successful. Our Core values are Compassion, Excellence, Innovation, Teamwork, Trust and Ownership.