Data Analyst (Finance, Risk & Fraud)

We're looking for a Data Analyst who wants to build the systems behind the numbers, not just report them — helping power how we detect fraud, manage risk, and keep financial reporting accurate.

You'll investigate transaction and financial data with Finance, Risk, and Compliance — strengthening reporting accuracy, catching fraud, and surfacing emerging risks before they turn into losses — and you'll help shape and validate the AI platforms that automate this work. (Our Data Platform Engineers build those systems; you define what they detect, measure, and flag, and check that their outputs hold up.) Some of the work is hands-on with pipelines and AI logic — if that's new to you, it's something you can grow into here, not a prerequisite.

In a fast-moving crypto market, the figures you produce are the numbers people make real decisions on, and the systems you help build protect our customers and the business directly. We value analysts who are curious, challenge assumptions, and dig into data to find what others miss — and we back that with mentorship and a clear path toward senior analyst and specialist tracks in risk, fraud, or financial data science.

Day to day, your work answers questions like: Do our financial reports reconcile and hold up to scrutiny? Which transactions look anomalous or fraudulent? Where is our risk exposure concentrated, and is it growing?

• Analyze transactions, financial trends, and customer activity to spot anomalies, fraud patterns, and risk exposures
• Dig into what drives key metrics, not just report on them

• Work closely with Finance, Risk, Compliance, and Operations to frame questions and evaluate controls and initiatives
• Translate business problems into structured analysis and actionable insight

• Develop and maintain dashboards and alerts that help teams monitor financial performance, fraud signals, and risk metrics — and explore the data themselves
• Improve how metrics and insights are communicated across the company

• Turn manual checks into automated monitoring that keeps reporting, fraud, and risk systems accurate and reliable
• Help design and validate the data and AI logic behind these platforms — anomaly detection, transaction monitoring, LLM/RAG analysis — plus the guardrails that keep their outputs trustworthy

• Work with the data team to improve data quality, metric definitions, and unified datasets
• Help build reliable data assets that support advanced analytics and AI initiatives (RAG, agentic AI)

• 2–4 years in data analytics or business intelligence
• Strong SQL
• Python for analysis and automation
• Experience with financial, transaction, or risk/fraud data
• Ability to turn ambiguous business questions into analytical investigations
• Interest in applying AI/ML to risk, fraud, and reporting problems (hands-on experience welcome, not required)
• Strong communication and cross-functional collaboration

• Financial services, fintech, or crypto experience, and familiarity with financial reporting or reconciliation
• Dashboarding tools (Power BI, QuickSight, Tableau)
• Exposure to fraud detection, anomaly detection, AML / transaction monitoring, or risk modelling
• Comfort contributing to automated data pipelines
• Cloud services and data-engineering tooling (AWS, dbt, Airflow)

• Finance, Risk, and Fraud teams clearly understand what drives their key metrics and exposures
• Decisions are increasingly data-informed
• Analytics assets are trusted, widely used, and continuously improved
• Our automated risk, fraud, and reporting platforms run reliably — high uptime, accurate outputs, and AI analysis teams act on with confidence

• Friendly and fun start-up work culture
• Convenient work location located in the heart of CBD area
• Generous annual leaves on top of national holidays
• Medical coverage including GP, Specialist, TCM, and more
• Self-care benefits and exciting fitness workshops/webinars
• Vibrant office with a well-stocked pantry

Find out more about Coinhako here [ and don't forget to visit our Careers Page [

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