Data Analyst

Data Analyst (Payments) — Data Office

We are looking for a Data Analyst to join our Data Office and be allocated to the Payments domain. You will partner with Payments, Risk/Fraud, Product, and Engineering teams to monitor payment flows, detect and prevent abuse, improve payment performance, and build scalable analytics foundations (data marts, metrics, and alerting).

Monitoring & alerting

• Own and build day-to-day monitoring of payment flows and key risk indicators (deposits/withdrawals, approval rates, chargebacks, reversals, disputes, processor incidents).
• Build and maintain alerting for anomalies and suspicious patterns; define thresholds, escalation rules, and investigation playbooks.

Payments analytics & research

• Investigate user behaviour across web and mobile apps, focusing on payment journeys, drop-offs, and abnormal patterns.
• Conduct ad-hoc analyses and deep dives to explain deviations, incidents, and emerging risks.
• Run research to discover new fraud patterns, weak signals, and optimisation opportunities.

Anti-fraud rules & algorithms (payments)

• Develop and iterate anti-fraud rules, scoring approaches, and detection logic for payment abuse.
• Evaluate rule quality and impact (false positives/negatives, loss prevention, customer experience impact) and drive continuous improvement.

Tools for monitoring team

• Build dashboards and tooling for the monitoring/operations team (investigation views, drill-downs, case lists, segmentation views).
• Translate operational needs into clear requirements for Engineering/Data Engineering.

Segmentation & unit economics

• Create customer segmentation by payments risk (behavioural, transactional, device/network, processor outcomes).
  
• Build unit economics of a paying user (fees/costs, chargeback/dispute losses, fraud losses, net contribution, cohorts).

Experimentation, metrics & data marts

• Design and analyse A/B tests related to payment flows, risk controls, and UX changes.
• Formulate requirements and actively participate in building payments data marts and “single source of truth” datasets.
• Improve the payments/product metrics system: definitions, documentation, and consistency.

• 3+ years of experience in data analytics (fintech/payments/risk is a strong plus).
• Strong SQL+Python and hands-on experience working with large datasets.
• Experience with monitoring/alerting, anomaly investigation, and KPI ownership.
• Practical understanding of fraud/risk analytics (rule-based detection, segmentation, basic modelling).
  Ability to communicate insights clearly and collaborate with cross-functional stakeholders.

• Experience with chargebacks/disputes, acquirers/processors, payment schemes, or AML-related analytics.
• A/B testing know-how (guardrails, bias, statistical pitfalls).
• Experience with product analytics tooling and event-based tracking.

• Databases: Snowflake, ClickHouse, MySQL, BigQuery
• Visualisation systems: Tableau, HEX
• Analytics tools: Amplitude
• Programming language: Python (pandas, numpy, scikit-learn)
• Interactive environments: Jupyter Notebook, HEX