Senior Data Scientist, People and Talent

About Airwallex Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide – including Brex, Rippling, Navan, Qantas, SHEIN and many more – with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale.

We hire successful builders with founder‑like energy who want real impact, accelerated learning, and true ownership. You bring strong role‑related expertise and sharp thinking, and you’re motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor. You’re humble and collaborative; turn zero‑to‑one ideas into real products, and you “get stuff done” end‑to‑end.

You use AI to work smarter and solve problems faster. Here, you’ll tackle complex, high‑visibility problems with exceptional teammates and grow your career as we build the future of global banking.

The Data Science team at Airwallex builds the data foundations, models, and decision‑support systems that help the business scale with speed and precision. We partner closely with leaders across the company to solve high‑impact problems through analytics, experimentation, machine learning, and data products.

Within this team, you'll be the dedicated data science partner for our People & Talent (P&T) function — the team that builds the systems, insights, and experiences behind how Airwallex attracts, grows, and retains exceptional people at global scale. You'll work closely with P&T, Finance, and Engineering to improve how HR and recruiting data is modelled, governed, and used, and help shape a more scalable, self‑serve, and AI‑enabled analytics ecosystem for people's decisions.

As Senior Data Scientist, People and Talent, you will own the People & Talent (P&T) data domain at Airwallex and turn our HR and recruiting data into a scalable analytics foundation for the business. You will define how headcount, hiring, and people metrics are modeled, governed, and accessed, and you will build the pipelines, dashboards, and self‑serve tools that power decisions across P&T, Finance, Revenue Strategy, and Engineering.

This role combines hands‑on data engineering and analytics with product thinking and stakeholder management: you will manage the roadmap for P&T data, act as the subject matter expert on people data, and drive continuous improvements in automation, governance, and AI‑enabled insights. You will also build context layers that make people data more accessible and meaningful across the business, and enable AI analytics capabilities that help P&T teams move faster and make better decisions.

• Own and manage all People & Talent (P&T) data assets, ensuring robust data models, pipelines, documentation, and governance across all HR and recruiting systems.
• Build and maintain scalable dashboards, reports, and self‑serve analytics supporting stakeholders in People & Talent, Finance, Revenue Strategy, and Engineering.
• Partner with cross‑functional teams to prioritize requests, manage the P&T analytics roadmap, and drive improvements in automation, data quality, and end‑user access workflows.
• Act as the subject matter expert on people data, supporting metric definition, troubleshooting, and user guidance, while upholding strict governance and privacy standards.
• Enable AI‑powered and self‑serve analytics use cases, and continuously identify opportunities to enhance the P&T analytics ecosystem to support global growth.

• 5+ years of experience in data science, analytics, or a related quantitative field, with end‑to‑end ownership of data models, pipelines, and dashboards in a production environment.
• Advanced degree (MS or PhD) in Statistics, Computer Science, Engineering, Economics, or a related field.
• Strong hands‑on proficiency in SQL and Python and/or R, with experience working with large and complex datasets, data transformations, and…