The future of money is hybrid and, we aren't waiting for it we’re building it.

From our crypto card and non-custodial wallet to advanced crypto processing, we create tools that bridge the gap between traditional finance and the decentralized world. We focus on what truly matters: moving value, paying, saving, and earning safely. We move fast with a product-led mindset, but we never compromise on compliance or clarity. If you enjoy distilling complex financial infrastructure into simple, elegant solutions that drive business growth rather than restricting it, you’ll feel at home here.

About the Role:
We are seeking a Senior Data Analyst with a strong financial background to drive our reporting and analytics capabilities. Working hand-in-hand with the Data Engineer, this specialist translates raw financial data from BigQuery into actionable insights, calculates P&L, manages reserves reporting, and automates data exports for external auditors.

Key Responsibilities:

Financial Reporting & P&L: Builds and maintains complex metrics trees, conversion funnels, and interactive dashboards using Looker or Grafana (ready to migrate to new BI) to track portfolio performance, P&L, and accounting summaries.
Auditor Exports & Compliance: Automates external analytics delivery and designs customized graphical and tabular reports tailored for compliance and auditing reviews.
Business Requirements: Gathers and formalizes business requirements for financial data marts, acting as the bridge between the Finance/Accounting department and the Data Engineer.
Data Quality Control: Designs a data quality (DQ) framework on the BI layer with automated validation checks and alerting mechanisms to ensure financial numbers are flawless.
Financial Modeling: Conducts comprehensive analysis of portfolio data, leveraging and consuming insights derived from Vertex AI (Gemini, Anthropic) models, and develops forecasting models (e.g., LTV, retention, expected loss, profitability) to support executive decision-making.
Ad-hoc Analytics: Performs complex financial turnover analysis, anomaly detection, and A/B testing evaluation using data stored in BigQuery, utilizing Python (Pandas, Numpy), Golang and expert-level queries.

Requirements:

3+ years of experience as a Data Analyst or Product/Financial Analyst in FinTech, Banking, or E-commerce.
Expert-level SQL skills for data extraction and complex aggregations in BigQuery.
Strong proficiency in Python (Pandas, Numpy) for data research and modeling.
Extensive experience with BI tools, preferably Looker or Grafana (or similar tools like Tableau, Power BI), and building dashboards for C-level executives.
Solid understanding of financial terminology, P&L structures, IFRS standards, and risk metrics (EAD, LGD, RWA).
Proven ability to write clear technical requirements for Data Engineering teams (understanding of DWH concepts)

For direct applicants only.