Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Staff Data Scientist, Algorithm (Fintech): Designing and implementing advanced algorithms to optimize payment conversion rates, fraud risk, and transaction costs with an accent on multi-objective optimization and ML productionization. Focus on implementing contextual bandits, causal inference, and A/B testing to drive product adoption and payment performance.
Location: Singapore
Company
Airwallex is a unified payments and financial platform for global businesses, providing integrated solutions for business accounts, payments, and treasury management.
What you will do
- Define and drive the technical strategy for multi-objective payments optimization (conversion, fraud risk, and cost).
- Act as the technical owner for complex cross-functional initiatives with broad business impact.
- Provide leadership on optimization algorithms, such as contextual bandits, and experimentation techniques like causal inference.
- Collaborate with engineering to design and deploy scalable ML systems and infrastructure to production.
- Influence product strategy and investment decisions by communicating complex data insights to stakeholders.
- Mentor and coach junior data scientists and engineers.
Requirements
- Advanced degree (PhD or MS) in Statistics, Engineering, Computer Science, Economics, or a related quantitative field.
- 5+ years of industry experience in data science or applied machine learning.
- Proven experience in experimentation and causal inference to drive product decisions.
- Proficiency in SQL and Python/R.
- Experience using LLMs, AI, and Agents to improve processes and ML models.
- Must be based in Singapore
Nice to have
- Strong experience in deploying ML systems to production.
Culture & Benefits
- Opportunity to work on high-impact problems directly influencing business outcomes.
- Collaboration within a talented, cross-functional team in a high-growth environment.
- Ability to drive the adoption of advanced data science techniques at scale.
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