[Hiring] Senior Applied Scientist @Upstart

Role Description

As a Senior Applied Scientist on the Servicing team, you will build predictive and causal models and translate their outputs into decisions that improve how loans are serviced. You’ll partner with Product, Engineering, and Servicing and Collections Operations to evaluate interventions and shape data-informed approaches to payment plans, loan modifications, communications, and autopay.

• Develop and evaluate machine-learning models that predict borrower repayment behavior and other servicing outcomes.
• Apply causal inference and experimentation to measure the impact of servicing interventions, including loan modifications and payment assistance.
• Translate model predictions and treatment-effect estimates into practical decision algorithms and actions.
• Partner with Product and Engineering on payment experiences, autopay, and borrower communications, and with Servicing and Collections Operations on collections strategy and agent-performance insights.
• Identify and develop machine-learning opportunities in servicing areas that have historically relied on manual optimization.
• Explain analytical choices, tradeoffs, and findings to technical and non-technical partners to inform high-stakes operational and product decisions.

Qualifications

• Graduate degree in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative field.
• Experience applying causal inference methods and experimentation to real-world decisions in an applied science or data science context.
• Applied statistics, probability, and experimental-design expertise used to build or evaluate models or interventions.
• Production-quality coding experience in Python, including data manipulation and algorithm implementation.
• 3+ years of experience conducting machine-learning, statistical-modeling, or applied quantitative research in an academic or industry setting.

Requirements

• PhD in a quantitative field (preferred).
• Experience with payment products or payment experiences, such as autopay, recurring payments, or payment plans (preferred).
• Experience with causal machine-learning methods or treatment-effect modeling (preferred).
• Experience with supervised learning, model evaluation, and feature engineering, especially with large or complex datasets (preferred).
• Experience taking work from exploratory analysis and experimentation through production model development while maintaining analytical rigor and model reliability (preferred).
• Ability to translate broad servicing or business problems into structured research questions and communicate complex findings as actionable recommendations (preferred).

Benefits

• Competitive compensation, including base pay, bonus opportunities, and annual equity grants that vest quarterly.
• Retirement benefits, including a 401(k) or Group Retirement Savings Plan with a company match of $2 for every $1 contributed, up to $15,000 annually (USD in the US, CAD in Canada).
• Employee Stock Purchase Plan (ESPP) with discounted stock purchase options for eligible employees (US only).
• Comprehensive health coverage, including medical, dental, vision, and wellness resources for US and supplemental health coverage for Canada.
• Health Savings Account contributions from Upstart for eligible plans (US only).
• Income protection benefits, including life insurance and disability coverage.
• Paid time off, sick leave, and company holidays, in line with local requirements.
• Paid family and parental leave to support caregiving and major life moments (duration varies by country).
• Family-centered benefits to support fertility, parenthood, and caregiving needs.
• Employee Assistance Program (EAP) offering mental health support and life-centered resources.
• Financial wellness resources, including access to financial planning tools and a financial concierge service (US Only).
• Annual wellness allowance to support your physical and emotional well-being and personal development.
• Annual productivity allowance to invest in relevant tools and resources.
• Connection and community through team events, all-company updates, and employee resource groups (ERGs).
• Onsite perks, including catered lunches and fully stocked micro-kitchens in offices.