Applied Scientist

Upstart

. Develop, train, and evaluate machine learning models to improve predictive performance and support lending decisions .

Posted 11/11/2026full-timeRemote • United States, CanadaJuniorMid-Level💰 $141,500 - $196,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and evaluating machine learning models, applying statistical methods, and analyzing large datasets to support data-driven lending decisions. Proficient in collaborating with cross-functional teams to implement and refine models in production environments.

Highest-signal resume keywords

Machine Learning Model DevelopmentStatistical Methods ApplicationPython ProgrammingFeature EngineeringSQL for Large-Scale Datasets

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningApplied StatisticsHypothesis TestingRegression AnalysisPredictive Modeling

Tools & Technologies

PyTorchTensorFlowScikit-LearnSQLDistributed Data Processing

Certifications & Qualifications

Bachelor's Degree in Computer ScienceBachelor's Degree in EngineeringBachelor's Degree in MathematicsBachelor's Degree in Statistics

Industry Keywords

Predictive PerformanceModel EvaluationFeature DevelopmentReproducible Scientific WorkflowsCollaboration with Scientists

Tech Stack

Tools & technologies

PythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Develop, train, and evaluate machine learning models to improve predictive performance and support lending decisions
Analyze large datasets to identify patterns, develop features, and inform modeling approaches
Design and execute experiments to assess model performance, validate hypotheses, and identify improvement opportunities
Collaborate with scientists and engineers to implement, monitor, and refine models in production environments
Document methodologies, communicate findings, and contribute to reproducible scientific workflows

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience
0–2 years of experience in machine learning, applied statistics, or a related quantitative field
Experience developing or evaluating machine learning models using Python
Experience applying statistical methods, including hypothesis testing, regression, or predictive modeling, to quantitative datasets
Knowledge of supervised learning techniques, model evaluation, and feature engineering
Familiarity with PyTorch, TensorFlow, or scikit-learn
Experience with large-scale datasets using SQL or distributed data processing tools
Advanced degree, ideally a PhD, in a quantitative field (preferred)

Benefits

Comp & perks

Competitive compensation, including base pay, bonus opportunities, and annual equity grants that vest quarterly
401(k) or Group Retirement Savings Plan with a company match of $2 for every $1 contributed, up to $15,000 annually
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 employees
Supplemental health coverage for Canada
Health Savings Account contributions for eligible plans (US only)
Life insurance and disability coverage
Paid time off, sick leave, and company holidays
Paid family and parental leave
Family-centered benefits supporting fertility, parenthood, and caregiving
Employee Assistance Program (EAP) with mental health support and life-centered resources
Financial planning tools and financial concierge service (US only)
Annual wellness allowance
Annual productivity allowance for relevant tools and resources
Team events, all-company updates, and employee resource groups (ERGs)
Catered lunches and fully stocked micro-kitchens at offices in the Bay Area, Austin, Columbus, and New York City