Staff Data Scientist, Algorithm, Growth

2 дн. назад

250k–299k USD / годСШАLeadHybrid

predictive modelingpersonalizationcausal inferencellmdata science

Staff Data Scientist role focused on growth, working on advanced data science and AI solutions to drive business growth.

is the AI-native financial operating system for a real-time, intelligent economy. More than 675,000 businesses, including McLaren Racing, Qantas, SHEIN, and TikTok, use us, directly or through our platform partners, to run their financial operations or build and monetize financial products of their own.
We started in Melbourne in 2015 to build the infrastructure global commerce runs on. We're the regulated backbone behind global payments: not by accident, but by design. A decade plus, 85+ licenses, and a financial infrastructure spanning North America, Europe, the Middle East, and Asia-Pacific.
We're co-headquartered in San Francisco and Singapore, with more than 2,300 people across 27 offices. We hire builders with founder-level energy, people who move fast with good judgment, dig in with real curiosity, and make calls from first principles rather than waiting to be told what to do. Read our operating principles to see it in full.

We’re seeking a Staff Data Scientist to partner closely with the Growth and Marketing teams to design, deploy, and iterate on high-impact data science solutions that drive measurable business outcomes. In this role, you will apply machine learning models to influence how we acquire, engage, and retain customers globally.
Your work will directly shape ’s growth strategy, influencing how we acquire, engage, and retain customers. You are naturally curious, business-oriented, and have a proven track record of translating data insights into actionable recommendations that strengthen brand presence and accelerate growth.
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 Marketing, Growth Product, Engineering, and cross-functional teams to inform, influence, support, and execute GTM strategy and investment decisions
Design and deploy a range of data science solutions—including predictive models, personalization and recommendation systems, LLM-powered applications, incentive optimization frameworks, and causal inference models—to drive measurable business outcomes
Apply machine learning and/or statistical models to measure causal impact of Marketing initiatives

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 machine learning and statistical modeling to drive data driven growth strategy
Hands on experience building, deploying, and maintaining machine learning models in production-grade systems (e.g., cloud-based services, real-time and batch pipelines).
Expert in data querying languages (e.g. SQL), scripting languages (e.g. Python); experience in schema design and dimensional data modeling a plus
Experience in technology, financial services and/or a high growth environment is advantageous

You’ll join the team during a critical period, where we are building a team that enables both global consistency in process, tooling and methodology and local flexibility and speed in execution. This is a great opportunity to shape the next phase of ’s growth.

The Growth Data Science team sits at the center of ’s growth engine, turning data and AI into a durable competitive advantage. We build and scale advanced solutions—from predictive modeling and personalization to LLM-powered systems, incentive optimization, and causal inference—to unlock step-change growth across the customer lifecycle.
Learn more about the data science team in this blog .
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