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Staff Data Scientist, Growth Analytics Engineering

United States, San Francisco - California

SpringCube

Full-time - Senior Engineer

Fintech

Posted 3 weeks ago

Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview
A leading global fintech platform provides unified payments and financial solutions to over 200,000 businesses worldwide. Leveraging proprietary infrastructure and software, the organization supports business accounts, payments, spend management, treasury, and embedded finance at a global scale. Headquartered in Melbourne with a team of 2,000+ across 26 offices, the company is backed by top investors and is valued at US$8 billion. The platform empowers major clients such as Brex, Rippling, Navan, Qantas, and SHEIN, enabling them to scale operations globally while driving innovation in financial technology.

Summary
The Staff Data Scientist will lead the Growth Analytics team, driving data-informed strategies that optimize acquisition, retention, and overall growth. This role combines technical leadership, mentorship, and cross-functional collaboration to deliver actionable insights and scalable analytics solutions for global expansion.

Responsibilities

  • Act as a technical partner to Growth, Marketing, Sales, and Data Science leaders to develop and implement growth strategies
  • Lead and mentor the team in applying data science techniques including root-cause analysis, statistical modeling, and experimentation
  • Design and implement scalable measurement frameworks to support data-driven decision-making across teams
  • Communicate complex insights and recommendations clearly to technical and non-technical audiences, ensuring findings drive business impact
  • Translate open-ended or complex business problems into structured, high-impact data science initiatives
  • Mentor and coach junior data scientists, serving as the technical owner on key cross-functional projects

Qualifications

Minimum qualifications:

  • At least 7 years of industry experience with a degree in a quantitative field (Statistics, Engineering, Sciences, Computer Science, Economics); advanced degree preferred (PhD or MS)
  • Proven experience mentoring or leading data science or analytics teams
  • Strong communication and interpersonal skills with the ability to influence strategy in high-growth, cross-functional environments
  • Track record of applying data science to drive measurable growth outcomes
  • Technical proficiency with SQL and Python/R; experience in data modeling is a plus
  • Experience in technology, financial services, or high-growth environments is advantageous

Preferred qualifications:

  • Experience mentoring teams in fast-paced, startup, or fintech environments

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.

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