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Data Scientist, GTM Engineering

SpringCube

Full-time - Senior Engineer

Fintech

United States, San Francisco - California

Published 3 weeks ago

Salary: 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 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
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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