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UpstartUpstartUnited States

Applied Scientist

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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