Senior Applied Scientist
Core
Build predictive and causal models to improve loan servicing outcomes, including payment plans, loan modifications, and borrower communications.
Role type
Senior Applied Scientist (Causal Inference & ML)
Builds
Data-informed approaches for collections, loan assistance, and payment experiences
Domain
Fintech / AI Lending
Deliverable
production ML models
Required skills
Causal inference, experimental design, applied statistics, Python, machine learning, model evaluation, feature engineering
Preferred skills
PhD in quantitative field, payment product experience, causal machine learning, treatment-effect modeling
Technologies
Python
Responsibilities
Develop and evaluate ML models predicting borrower repayment; Apply causal inference to measure intervention impact; Translate predictions into decision algorithms; Partner with Product/Engineering on payment experiences; Identify ML opportunities in manual optimization areas; Explain analytical choices to technical and non-technical partners
Seniority
Senior, hands-on IC
