Airwallex - Staff Data Scientist
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Requirements
• We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory. • 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) • Experience in schema design and dimensional data modeling a plus • Experience in technology, financial services and/or a high growth environment is advantageous • Applicant Safety Policy: Fraud and Third-Party Recruiters • To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page. • Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary. • Equal opportunity • Equal opportunity
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 • Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.
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