Clair builds an on-demand pay product embedded into payroll systems, powered by ML-driven credit models and financial data integration. The tech stack—PyTorch, XGBoost, scikit-learn, dbt, Snowflake—signals a data science–heavy operation focused on credit underwriting and risk modeling. Active hiring is concentrated in data roles (7 open), and core projects span predictive feature engineering, credit model development, and earned wage access, indicating a company scaling the ML infrastructure needed to move workers from a two-week payroll cycle to immediate access.
Clair is an AI-driven fintech company offering on-demand pay solutions that embed into employer payroll systems. Founded in 2019 and based in New York, the company serves mid-market employers seeking to offer earned wage access to employees. The platform combines compliance-first lending infrastructure with real-time financial data integration and credit risk modeling. Core operations span credit underwriting systems, payroll processing, and data science platforms. The company is 51–200 employees and hiring across data, engineering, and product teams in the United States.
Clair uses AWS, Snowflake, Python, PyTorch, XGBoost, scikit-learn, dbt, SQL, Tableau, Power BI, Plaid, Zendesk, Gusto, and QuickBooks. The ML toolkit (PyTorch, XGBoost, scikit-learn) reflects heavy credit modeling work.
Active projects include predictive feature engineering, next-generation credit models, earned wage access, secure lending systems, model deployment and monitoring, and data science platform development.
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