Head of Data.Employment

The data team capacity needed to scale across African operations to support growing operational and BI needs, requiring 2 senior hires alongside a strong data engineer.

Authored the job scopes, technical requirements, and business cases justifying the senior hires to the leadership. Designed and ran technical interviews and assessments, evaluated 50+ candidates, negotiated offers end-to-end, and coordinated onboarding for 12 total hires with tooling access, team integration, and 30/60/90-day ramp milestones.

The data team needed a curated reference of high-impact use cases to prioritize roadmaps, drawing inspiration from how Gojek, Grab, and Uber operate at scale and adapting to Gozem’s Sub-Saharan markets.

Catalogued 100+ use cases across demand forecasting, driver scoring, fraud detection, surge pricing, and route optimization. Selected the top 15 and adapted each with Gozem-specific feasibility, data availability, and applicability assessments. Defined success metrics, technical challenges, infrastructure requirements, and estimated business impact, structured as a living reference for the data and product teams.

Gozem Money (fintech vertical) needed real-time fraud monitoring, a fintech-grade data warehouse, and a reporting layer to support mobile payment operations and regulatory needs across African markets.

Designed and supervised deployment of a micro-batch processing pipeline monitoring anomalous patterns, fraud signals, and threshold breaches. The system surfaces ~150 incidents per month and flagged a major fraud worth 20M+ CFA. Built the fintech data warehouse for Togo operations, powered by ETL/ELT pipelines and data models as the foundational layer for financial analytics, regulatory submissions, and stakeholder dashboards (transaction volumes, product adoption, revenue, cohorts). Established data quality pipelines and documented data models, reporting glossary, and metric definitions.

Non-technical users across operations, finance, product, and customer support depended on the central data team for routine reporting and ad-hoc queries, creating a bottleneck.

Assessed data literacy and exploration needs across all Gozem markets. Coordinated configuration of a no-code query and exploration layer (Metabase) integrated with Gozem’s central data warehouse. Adoption reached 12+ active manager users, halving routine query volume on the central data team.

Delivery-agent positioning across high-demand zones was unmanaged, and incentive payments required manual finance intervention plus heavy customer-support load to resolve disputes.

Modeled demand by zone, time-of-day, and event type to identify underserved areas. Designed a performance framework (acceptance rate, completion rate, zone presence, quality scores) and end-to-end payment automation from incentive calculation through disbursement instructions. Built a justification database with pre-computed data points enabling support to resolve cases within 24h. Cut incentive-related ticket volume nearly in half through pre-emptive payment automation.