Manager, Risk Data Operations

About the team

The Product team at Airwallex is a group of passionate builders and problem-solvers who are obsessed with crafting sacustomer-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

As Manager, Risk Data Operations, you will be the go-to data operations partner for our Regulatory Compliance and Financial Crime Compliance teams, impacting 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.

• Work with Data Engineering to define automated test suites and manual QA playbooks that must pass before reports are submitted to regulators.

• Leverage snapshotting and versioning approaches so that “as‑of” historical reports can be regenerated and explained consistently during RFIs, audits, or supervisory exams.

• 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

• Lead cross‑functional collaboration, act as the primary analytics partner, turning open‑ended regulatory and risk questions into structured analytical projects and roadmaps.

• 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 proven risk management experience or equivalent, including analytics, modeling implementation, and stakeholder management

• 5+ years of hands-on experience extracting and manipulating large data with SQL, experience with scripting in Python, Shell or R

• Experience building visualizations using large datasets and multiple data sources using Looker or Tableau

• 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 

• Familiarity with data modelling for fintech products such as payments, FX, wallets, cards, and lending, including concepts like transaction lifecycles, balances, FX rates, stored value, and chargebacks.

• Exposure to model risk or AI/ML governance (e.g. model inventories, validation, monitoring) and an interest in how these frameworks intersect with regulatory reporting and compliance analytics.

• Intuitive, organized analytical thinker, with the ability to perform detailed analysis. Knowledge of analytical tools and use of data to validate strategies or hypotheses

• Experience working with cross-functional, geographically distributed teams, managing by influence is a plus