Staff Machine Learning Engineer, Credit Products (Square Financial Services)

Description:

• Apply scientific and statistical methods to evaluate new customer segments and improve underwriting performance.
• Lead ML operations and infrastructure initiatives, including data ingestion scaling and support for more advanced model architectures.
• Design and implement the full credit modeling stack from data signal curation through production decisioning logic.
• Use data science techniques to turn messy external and internal data sources into usable modeling inputs.
• Identify and execute improvements to credit policy that improve customer outcomes and portfolio performance.
• Support updates to existing models and troubleshoot issues in a real-time production environment.
• Operate within the requirements of a regulated banking environment, balancing innovation with safety, soundness, and compliance.

Requirements:

• 8+ years of related experience with a bachelor's degree, 6+ years with a master's degree, or a PhD with 3+ years of experience in machine learning or statistical models deployed in production.
• Degree in a technical field such as Computer Science, Mathematics, Statistics, Physics, or Engineering.
• Strong quantitative intuition and data visualization skills.
• Proven ability to conduct sophisticated ad-hoc and exploratory analysis.
• Full-stack proficiency preferred, with the ability to work across data pipelines and production-grade software architecture.
• Ability to communicate clearly with both technical and non-technical audiences, including executive stakeholders.
• Pragmatic problem-solving approach with the ability to choose the right tool while navigating business, technical, and regulatory constraints.
• Experience with tree-based models and gradient boosting is helpful but not required.
• Demonstrated track record of scientific research or an advanced degree is strongly preferred.

Benefits:

• Market-based pay with U.S. salary zones; starting salary ranges from $194,500 to $343,100 USD depending on location.
• Remote work.
• Medical insurance.
• Flexible time off.
• Retirement savings plans.
• Modern family planning benefits.
• Reasonable accommodations during the recruitment process.

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