Senior Data Scientist, Anaytics (Risk & Compliance)

ABOUT AIRWALLEX Airwallex is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own. We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific. We're co-headquartered in San Francisco and Singapore, with more than 2,300 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles https://www.airwallex.com/en-us/operating-principles to see it in full.   ABOUT THE TEAM The Product team at Airwallex is a group of passionate builders and problem-solvers who are obsessed with crafting customer-centric solutions that empower businesses to operate anywhere, anytime. We combine technical expertise with a deep understanding of our customers' needs to design and build unified, intuitive, and scalable products. As a team, we thrive in a collaborative and fast-paced environment, constantly iterating and pushing boundaries to deliver exceptional product experiences. We partner closely with legal, regulatory, financial crime compliance, product, engineering and commercial teams to help Airwallex grow safely and sustainably. Our work spans regulatory reporting, financial crime compliance, enterprise risk management, data & privacy and more; all under a fast-evolving global regulatory landscape. We’re a high-impact, high-trust team that thrives on solving complex problems to support Airwallex’s global ambitions. WHAT YOU'LL DO This is not a traditional reporting role. You will own the analytical layer of Airwallex's regulatory data infrastructure, defining what "correct" means, building systems that prove it, and working at the intersection of data engineering, compliance logic, and product intelligence. As Senior Data Scientist, Analytics (Risk & Compliance), you will be the go-to analytics partner for our Regulatory Compliance and Financial Crime Compliance teams, impact across our global footprint. You’ll help transform how Airwallex manages regulatory reporting and risk oversight by building robust data foundations, validation frameworks, and self-service analytics that regulators, auditors, and senior leaders can rely on. This role is based in Singapore, with the opportunity to relocate and work in a fast-growing, globally connected tech ecosystem. RESPONSIBILITIES - Lead analytics and data design for priority regulatory reports (e.g. regulatory compliance, financial crime, and financial regulatory returns), from requirement translation through to data logic, testing, and go‑live. - Partner with Regulatory Compliance, FCC, Finance, DataOps and Data Engineering to standardise how we use common dimensions (accounts, FX, products, entities) across reports, leveraging the regulatory reporting data foundation. - Co-design data models and mart-layer logic with Data Engineering — not just a consumer of tables, but an active voice in how reporting dimensions are structured, tested, and versioned upstream. - Work with Data Engineering to define automated test suites and manual QA playbooks that must pass before reports are submitted to regulators. - Conduct deep‑dive analyses when anomalies, RFIs, or audit findings arise – quantifying impact, identifying root causes across products/entities, and proposing remediation options. - Shape requirements for a scalable regulatory reporting and risk analytics platform - Champion best practices in analytical rigour, documentation, and validation for colleagues working on risk and compliance topics; provide informal mentorship to analysts and data scientists in adjacent teams. WHO YOU ARE We're looking for people who meet the minimum requirements for this role. The preferred qualifications are great to have, but are not mandatory. Minimum qualifications: - Bachelor's degree in Mathematics, Statistics, Operations Research, Finance, Economics or related quantitative discipline - 5+ years of hands-on experience extracting and manipulating large data with SQL, experience with scripting in Python, Shell or R - 5+ years proven risk management experience or equivalent, including analytics, modeling implementation, and stakeholder management - Familiarity with analytics engineering practices: writing modular, tested, documented SQL transformations (e.g. dbt or equivalent), and thinking in layers: source → staging → marts - Experience building exploratory and production-grade analytics using modern data tools (e.g. Hex, Evidence, or notebook-style environments where SQL, Python, and visualisation coexist in the same workflow) - Excellent communication and stakeholder-management skills: able to explain technical data topics to non-technical audiences, document assumptions clearly, and influence cross-functional partners across Legal, Risk, Compliance, Finance, and Engineering Preferred qualifications: - Direct experience working on regulatory reporting for risk and compliance domain - Hands-on experience with dbt (models, tests, docs, macros) and a modern data warehouse (BigQuery, Databricks, or Snowflake); able to own a data model end-to-end, not just query existing tables - Understanding of data pipeline design: knows when a problem belongs in the transformation layer vs. the application layer vs. the reporting layer — and can have that conversation with a Data Engineer as a peer - Exposure to model risk or AI/ML governance (e.g. model inventories, validation, monitor…