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Company Overview
A leading global payments and financial platform empowers over 200,000 businesses worldwide with fully integrated solutions for business accounts, payments, spend management, treasury, and embedded finance. Headquartered in Melbourne, the organization operates 26 offices globally with a team of over 2,000 technology professionals. Backed by top-tier investors, the company is focused on building the next-generation global payments and financial infrastructure, driving innovation in fintech, AI, and data science.
About the Team
The GTM Data Science team is a collaborative group of analytics and data science professionals focused on driving commercial success. Working closely with Product, Growth, and Commercial teams, the team leverages data-driven methods to uncover insights, optimize revenue, and transform analytical findings into scalable business impact.
Responsibilities
Partner with Product, Growth, and Commercial teams to design and implement data science solutions that drive revenue acceleration and improve commercial outcomes
Lead exploratory analyses to identify revenue levers, emerging trends, and operationalize insights into robust, repeatable workflows
Develop and manage revenue forecasting models and performance insights (e.g., pipeline health, conversion and retention drivers, scenario planning) to serve as a “source of truth”
Apply advanced causal inference techniques such as Difference-in-Differences, synthetic control, and DoubleML to estimate impact and guide strategy when RCTs are infeasible
Design and deploy AI-enabled solutions across the sales and customer lifecycle to support sales effectiveness, retention, and expansion initiatives
Translate complex modeling results into clear business actions and communicate findings to both technical and non-technical stakeholders, including executives
Collaborate with and mentor junior team members, sharing technical expertise on high-impact, cross-functional projects
Qualifications
Minimum Qualifications
Advanced degree (MS or PhD) in a quantitative field (Statistics, Computer Science, Engineering, Economics, or related discipline) with at least 3 years of industry experience
Strong analytical intuition and problem-solving skills, capable of translating complex business questions into structured analytic projects
Excellent communication skills, able to distill technical insights for varied audiences and influence commercial strategy
Technical proficiency in SQL and Python and/or R; experience with causal inference and revenue forecasting is essential
Experience applying data science in technology, financial services, or high-growth business environments
Preferred Qualifications
Experience with Databricks or similar cloud data platforms
Familiarity with Hex or other notebook-based analysis tools
Background in B2B business models, CRM, pipeline, or RevOps data
Experience mentoring analysts or data science talent in fast-paced startup or fintech environments
Disclaimer
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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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