NymCard’s mission is to enable fintech and financial innovators to launch frictionless payment programmes with our modern infrastructure, at record speed. Our open API modern card issuing platform provides flexibility and control to issue cards, authorise transactions, and manage payment operations with just one integration and one partner.
We are a team of industry experts and technology innovators who take a dynamic approach to solving complex industry challenges. NymCard has an open and collaborative work environment and together we make up the NymCardian Nation. We power possibilities for our customers and each other by bringing the best talent together to do the best quality work we can.
The Role
We are hiring a Data Analyst focused on financial data to build trusted datasets and insights for Finance, FP&A, and Leadership. You will connect platform events with scheme and processor files, align outputs to the ledger and ERP, and publish clear reporting on revenue, fees, margins, cash, and unit economics. You will improve data models, document logic, and keep evidence audit ready. Success looks like accurate tie outs, faster month end reporting, reliable dashboards, and simple narratives that drive decisions.
What You’ll Be Doing
- Model core finance data: design and maintain marts for revenue, scheme fees, processor costs, chargebacks, settlements, and cash.
- Build with Python: create reusable data transforms and validation utilities in Python using pandas or polars, write unit tests, package common logic, and schedule jobs.
- Reconcile sources: match Visa and Mastercard statements and processor files to platform data and the GL. Track breaks to closure with reproducible queries and scripts.
- Month end support: deliver cut, validated datasets for journals, accruals, and deferrals. Provide concise variance explanations to Finance.
- Profitability views: publish client, product, and country margins. Explain movement against plan and highlight actions.
- Forecast inputs: produce run rate and cohort views for FP&A models including volume, ARPU, take rates, and cost curves.
- Billing checks: validate billable events against contracts and pricing rules. Confirm invoice inputs and corrections.
- Data quality and controls: define tests for freshness, completeness, and accuracy. Add alerts and owners.
- Automation and documentation: standardise transforms in SQL and dbt or similar. Write clear readme and logic notes. Version everything in Git.
- Dashboards and MI: build Power BI, Looker, or Tableau dashboards for leadership. Keep definitions and filters consistent.
- Stakeholder partnership: work daily with Finance, FP&A, Product, Operations, and Banking Services to prioritise and validate changes.
- Audit readiness: maintain indexed evidence for numbers and logic including samples, queries, scripts, and sign offs.
What You Bring
- 3 to 6 years in analytics for fintech, payments, or banking with hands on financial datasets.
- Python expertise is required for data preparation, validation, automation, and analysis. You write clean, tested code and use virtual environments and package management.
- Excellent SQL and data modeling skills for large normalized and star schemas.
- Experience with a modern warehouse such as Snowflake, BigQuery, or Redshift, plus dbt or a similar ELT framework.
- Working knowledge of IFRS concepts that affect data logic including revenue recognition, accruals, provisions, and foreign currency.
- Comfort reading scheme and processor files and tying them to the ledger, invoices, and settlement statements.
- Strong dashboarding in Power BI, Looker, or Tableau with clear definitions and refresh governance.
- Clean documentation habits and an eye for data quality, lineage, and ownership.
- Clear writing and steady stakeholder communication under deadlines.
Nice to have
- Experience with Airflow or Prefect for orchestration.
- Chargebacks data exposure and recovery analytics.
- Knowledge of unit economics and pricing analysis for B2B fintech.
- Basic statistical testing and cohort analysis in Python.
Bonus Points
- Hybrid working model: In-office collaboration for design reviews, workshops, and team days, with flexible remote time for deep work. Clear expectations on core hours and availability.
- Ownership and growth: Small teams and direct access to decision makers. End-to-end responsibility for your area, support for certifications and learning, and progression based on outcomes.
- Cross-border exposure: Work with clients and partners across MENA and beyond. Gain hands-on experience with schemes, banks, and regulators, and broaden your domain expertise.
- Real product and business impact: Build for a live issuing platform used by fintechs. See measurable results on performance and revenue within weeks, and celebrate wins backed by data.
