Conduct machine learning and statistical research to improve unsecured underwriting models, evaluating enhancements through rigorous experimentation and validation. The role requires a graduate degree in a quantitative field, Python modeling experience, and 0–2 years of applied research experience.
142k – 196k/yr
RemoteEntry levelAI Research
About the role
Responsibilities
Research machine learning and statistical approaches that improve the predictive performance of unsecured underwriting models.
Design, implement, and evaluate model enhancements using rigorous experimentation and validation methods.
Analyze model performance and downstream effects to confirm that proposed changes improve decisioning reliably.
Partner with engineering teams on technical reviews, implementation, and deployment.
Translate research findings into clear recommendations, documented methodologies, and production-ready solutions.
Requirements
Graduate degree in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative field.
0–2 years of experience conducting machine learning, statistical modeling, or applied quantitative research in an academic or industry setting.
Experience developing and evaluating machine learning or statistical models using Python.
Knowledge of probability, statistics, and machine learning methods.
Experience designing experiments or validation analyses to assess model accuracy, reliability, or predictive performance.
Nice-to-haves
PhD in a quantitative field.
Knowledge of supervised learning, model evaluation, and feature engineering techniques.
Experience working with large or complex datasets and translating research concepts into implemented solutions.
Ability to balance research velocity with analytical rigor, model reliability, and responsible decision-making.
Strong written and verbal communication skills, with the ability to explain technical concepts clearly and collaborate with cross-functional teams and stakeholders.
Compensation and Benefits
Anticipated base salary range: $141,500–$196,000 USD. Actual base pay varies by geographic location, skills, experience, education, and training.
Target bonuses, equity compensation, and benefits.
Medical, dental, and vision coverage, with Health Savings Account contributions for eligible US plans.
401(k) or Group Retirement Savings Plan with company match.
Employee Stock Purchase Plan for eligible US employees.
Life and disability insurance.
Paid time off, sick leave, company holidays, and paid family and parental leave.
Family-centered fertility, parenthood, and caregiving benefits.
Employee Assistance Program and financial wellness resources.
Annual wellness and productivity allowances.
Remote work with regular team onsites and in-person meetings.
Skills
Machine LearningStatistical ModelingPythonprobabilityStatisticssupervised learningfeature engineeringModel Evaluationexperiment designvalidation analysispredictive modelinglarge-scale data
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