Senior Applied Scientist — ML for Smarter Loan Servicing

Upstart; United States; Teletrabalho; USD 168 000 - 232 000; Tempo integral

Resumo da oferta

Upstart is seeking a Senior Applied Scientist for its Servicing team to build predictive and causal models that improve loan servicing decisions. You will translate outputs into actionable rules affecting repayment, autopay, and borrower communications.

You’ll partner with Product, Engineering, and Operations to implement data-informed interventions, evaluate experiments, and scale models across the US remote work landscape.

Qualificações

• Experience applying causal inference methods and experimentation to decisions.
• Strong background in statistics, probability, and experimental design.
• Production-quality Python coding experience.
• 3+ years in ML, statistical modeling, or applied quantitative research.
• PhD preferred in a quantitative field.

Responsabilidades

• Develop and evaluate machine-learning models that predict borrower repayment behavior and servicing outcomes.
• Apply causal inference and experimentation to measure impact of servicing interventions.
• Translate model predictions and treatment effects into practical decision algorithms.
• Partner with Product and Engineering on payment experiences, autopay, and borrower communications.
• Collaborate with Servicing and Collections Operations on strategy and insights.
• Identify ML opportunities in servicing areas historically optimized manually.

Conhecimentos

Causal inference expertise

Statistics / probability

Python programming

Machine learning / modeling

Experiment design

Communication of analytics

Formação académica

Graduate degree in quantitative field

PhD in a quantitative field

Ferramentas

Python

Descrição da oferta de emprego

Upstart is seeking a Senior Applied Scientist for its Servicing team to build predictive and causal models that improve loan servicing decisions. You will translate outputs into actionable rules affecting repayment, autopay, and borrower communications.

You’ll partner with Product, Engineering, and Operations to implement data-informed interventions, evaluate experiments, and scale models across the US remote work landscape.