Senior Applied Scientist

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Design and assess machine-learning models aimed at predicting borrower repayment behaviors and various servicing outcomes.

• Utilize causal inference and experimentation techniques to evaluate the effects of servicing interventions such as loan modifications and payment assistance.

• Convert model predictions and treatment-effect estimates into actionable decision algorithms and strategies.

• Collaborate with Product and Engineering teams on payment experiences, autopay features, and borrower communication strategies.

• Work alongside Servicing and Collections Operations to enhance collections strategies and provide insights into agent performance.

• Recognize and cultivate machine-learning opportunities in servicing sectors that have traditionally depended on manual optimization.

• Articulate analytical decisions, trade-offs, and results to both technical and non-technical stakeholders to guide critical operational and product decisions.

⛳️ Requirements

• A graduate degree in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative discipline.

• Proven experience in applying causal inference techniques and experimentation to real-world decision-making within an applied science or data science environment.

• Proficiency in applied statistics, probability, and experimental design for building or assessing models or interventions.

• Hands-on coding experience in Python with a focus on data manipulation and algorithm implementation.

• A minimum of 2 years of experience in machine-learning, statistical modeling, or applied quantitative research in an academic or industry context.

• A PhD in a quantitative field is preferred.

• Preferred experience with payment products or payment-related experiences.

• Familiarity with causal machine-learning techniques or treatment-effect modeling is preferred.

• Experience in supervised learning, model evaluation, and feature engineering is preferred.

• A track record of guiding projects from exploratory analysis and experimentation to production model development is preferred.

🏝️ Benefits

• Competitive compensation package, which includes base salary, bonus opportunities, and annual equity grants that vest quarterly.

• 401(k) or Group Retirement Savings Plan featuring a company match of $2 for each $1 contributed, capped at $15,000 annually.

• Employee Stock Purchase Plan (ESPP) offering discounted stock purchase options for eligible employees (US only).

• Comprehensive medical, dental, vision, and wellness resources.

• Supplemental health coverage available for Canada.

• Contributions to Health Savings Accounts for eligible plans (US only).

• Life insurance and disability coverage provided.

• Paid time off, sick leave, and company holidays included.

• Paid family and parental leave benefits.

• Support for fertility, parenthood, and caregiving needs.

• Employee Assistance Program offering mental health support and life-centered resources.

• Financial planning tools and concierge service available for employees (US only).

• Annual wellness allowance offered.

• Annual productivity allowance for relevant tools and resources provided.

• Team events, all-company updates, and employee resource groups foster a collaborative environment.

• Catered lunches and fully stocked micro-kitchens available at office locations.