Block
Financial Services
StaffMachineLearningEngineer,CreditProducts(SquareFinancialServices)
“Staff Machine Learning Engineer, Credit Products (Square Financial Services) at Block. Skills: Machine Learning, Statistical Models, Credit Underwriting, Production Deployment, Full-stack Development. Apply a rigorous scientific mindset to the challenge of underwriting new customer segments, involving the evaluation of alternative external data sources and the deployment of advanced architectures to enhance predictive accuracy.. Lead complex ML Operations and Infrastructure initiatives that adva”
Industry & Context.
Pragmatic approach to problem-solving; Making sense of messy datasets and bringing clarity to business decisions.
Operate effectively within the framework of a regulated bank (SFS)
What They're Looking For.
Must Have
Minimum of 8 years of related experience with a Bachelor's or 6 years and a Master's or a PhD with 3 years experience, with a focus on developing and deploying machine learning and statistical models in production environments., A degree in a technical field (e. g. , Computer Science, Mathematics, Statistics, Physics, or Engineering)., quantitative intuition and data visualization skills, with a proven ability to conduct sophisticated ad-hoc and exploratory analysis., The versatility to communicate clearly with both technical and non-technical audiences, particularly in the context of high-visibility projects and executive stakeholders., A pragmatic approach to problem-solving, with a willingness to utilize whichever tool is most appropriate for the situation while balancing complex business, technical, and regulatory constraints.
Nice to Have
preference for candidates with a demonstrated track record of scientific research or an advanced degree., Full-stack proficiency preferred, including the ability to contribute across the entire technical stack—from data pipelines to production-grade software architecture., Experience with tree-based models and gradient boosting is helpful but not we value the ability to adapt and learn new methodologies as the credit landscape evolves.
What You'll Do.
Apply a rigorous scientific mindset to the challenge of underwriting new customer segments
involving the evaluation of alternative external data sources and the deployment of advanced architectures to enhance predictive accuracy.
Lead complex ML Operations and Infrastructure initiatives that advance our modeling capabilities
such as scaling data ingestion or enabling the use of more complex neural networks.
Design and implement the full credit modeling stack
taking responsibility for the entire lifecycle of credit decisioning and ensuring models are robustly integrated into production environments.
Use data science techniques to leverage new data sources for modeling
making sense of messy datasets and bringing clarity to business decisions.
Identify and execute material improvements to credit policy
applying an analytical lens to determine where technical or logic shifts can yield significant positive outcomes for the customer and the bank’s portfolio.
Support team members in ad-hoc and scheduled updates to existing models
and help troubleshoot issues in a real-time production environment.
Operate effectively within the framework of a regulated bank (SFS)
balancing rapid innovation with the requirements of safety
How You'll Work.
Team & Collaboration
Support team members in ad-hoc and scheduled updates to existing models; Communicate clearly with both technical and non-technical audiences, particularly in the context of high-visibility projects and executive stakeholders.
Communication Scope
Communicate clearly with both technical and non-technical audiences
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