Staff Data Scientist

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 100,000 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.

Proudly founded in Melbourne, we have a team of over 1,500 of the brightest and most innovative people in tech located across more than 20 offices across the globe. Valued at US$5.6 billion and backed by world-leading investors including Sequoia, Lone Pine, Greenoaks, DST Global, Salesforce Ventures and Mastercard, Airwallex is leading the charge in building the global payments and financial platform of the future. If you're ready to do the most ambitious work of your career, join us.

About the team

As a global team, we span across Australia, China, USA, and Singapore, revolutionizing applied data science, data engineering and platform solutions to support Airwallex's rapid growth. You will collaborate with a diverse range of cross-functional partners, including Product, Engineering, Marketing, Sales, Finance, and more, to tackle complex data problems and shape the future of fintech.

What you'll do

Responsibilities:

• Uplevel the data science team by providing technical mentorship, assuming hands-on leadership to resolve complex problems, and setting the vision for longer term direction.
• Serve as a strategic thought leader with cross-functional teams to inform, influence, support, and execute strategy and investment decisions.
• Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products.
• Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.

Who you are

We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory.

Minimum qualifications:

• 7+ years industry experience and an advanced degree (PhD or MS) in a quantitative field (e.g. Statistics, Engineering, Sciences, Computer Science, Economics).
• Experience with communicating the results of analyses to leadership teams and cross-functional teams to influence the strategy.
• Technical mentorship experience with machine learning and experimentation in an industry setting.
• Expert in data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R).

Preferred qualifications:

• Experience in schema design and dimensional data modeling a plus.
• Experience in technology, financial services and/or a high growth environment is advantageous.