Drimva

Airwallex

Staff Data Scientist, Algorithm, Growth

$250K–$299K

US - San Francisco · Hybrid · Staff · Full-time · Posted Oct 12, 2026

Experience
7+ years of industry experience.
Education
Advanced degree, such as a PhD or MS, in a quantitative field such as Statistics, Engineering, the Sciences, Computer Science, or Economics.

About the job

Build and lead production data science systems that use machine learning and AI to improve customer growth and business outcomes, while measuring the impact of growth initiatives.

What you'll do

  • Design, deploy, and iterate on predictive models, recommendation and personalization systems, LLM applications, incentive optimization, and causal inference models.
  • Partner across teams to inform growth strategy, investment decisions, and go-to-market plans; measure the impact of marketing and growth initiatives.
  • Provide hands-on technical leadership, mentorship, and direction for the data science team.

What they ask for

  • 7+ years of industry experience and an advanced degree (such as a PhD or MS) in a quantitative field.
  • Expert knowledge of machine learning and statistical modelling for growth strategy; experience applying them to measure causal impact of marketing or growth initiatives.
  • Hands-on experience building, deploying, and maintaining production machine learning models, including cloud services and real-time or batch pipelines.
  • Strong experience with SQL, Python, AI harnesses, and building AI agents.

Nice to have

  • Experience with schema design and dimensional data modelling.
  • Experience communicating recommendations to leadership and cross-functional teams; technical mentorship experience is also preferred.

Pay

$250K – $299K USD base salary; equity and bonus offered, amounts not stated.

Tools

SQL, Python

AI focus

Build LLM-powered applications, AI agents, and AI analytics harnesses, including context retrieval, evaluation, validation, and governance; create systems that use AI and machine learning to influence product and business outcomes.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)