Original listing text, shown exactly as published by the company.
About the role
We are looking for a Data Analyst who combines strong SQL and analytical skills with business and compliance understanding.
This is a data-first, business-impact role where you will
- Independently analyze transaction and risk data
- Generate insights
- translate those insights into risk rules, system logic, and operational decisions
Key Responsibilities
- Analyze large-scale transaction datasets using SQL to identify fraud, AML, and compliance risk patterns.
- Translate analytical findings into clear business actions (rule tuning, thresholds, workflows, policy inputs).
- Work with Compliance, Risk, and Product teams to convert regulatory requirements into data logic and system rules.
- Evaluate effectiveness of risk controls using data (alert rates, false positives, precision/recall, conversion impact).
- Design, build, and maintain dashboards and reporting that drive decision-making.
- Perform deep-dive analyses and investigations to support financial crime initiatives.
- Identify gaps and inefficiencies in current processes and recommend data-driven improvements.
- Partner with engineering to implement scalable and auditable decisioning systems.
Requirements
- 3–6 years of experience in data analytics, risk, fraud, compliance, or financial services.
- Strong proficiency in SQL (mandatory) ability to independently extract, join, and analyze large datasets.
- Proven ability to connect data insights to business decisions and outcomes.
- Experience building dashboards / visualizations (Tableau, Power BI, Looker, or similar).
- Strong analytical thinking with a problem-solving, data-to-decision mindset.
- Ability to work across technical and non-technical stakeholders.
- Experience in fraud detection, AML, or transaction monitoring systems.
- Exposure to rule engines, decision systems, or risk platforms.
- Familiarity with Python (Pandas, NumPy) for data analysis.
- Understanding of experimentation / threshold tuning / performance optimization.
What Success Looks Like
- You independently query and break down complex datasets without relying on others.
- You move from data → insight → action quickly and clearly.
- You improve risk systems with measurable impact (e.g., reduced false positives, improved detection rates).
- You think in terms of signals, patterns, and system behavior, not just reports.
What We’re Really Looking For
- You don’t wait for data - you pull it yourself.
- You don’t just present numbers -you recommend actions.
- You can connect data → risk insight → rule/system change → measurable outcome.
- You are comfortable operating across data, business, and system logic.
