Remote Applied Scientist — AI for Smarter Lending

Upstart; Columbus, Austin, San Francisco (OH, TX, CA); Remoto; USD 142.000 - 196.000; Tempo pieno

Vantaggi offerti da questo lavoro

Competitive pay & equity

Retirement benefits

ESPP (US)

Health coverage

Paid time off

Parental and family leave

Descrizione del lavoro

Upstart is seeking an Applied Scientist to develop and evaluate machine learning models that improve lending decisions. You will work with scientists, engineers, and cross-functional partners to turn complex data into measurable improvements and scalable solutions.

You will analyze large datasets, design experiments, and help deploy models in production while documenting methodologies for reproducibility. A strong foundation in statistics and ML with Python is required, plus collaboration across

Competenze

• Bachelor’s degree in CS, Engineering, Math, Statistics, or related field; or equivalent practical experience.
• 0–2 years in machine learning, applied statistics, or related quantitative field.
• Experience developing or evaluating ML models using Python.
• Experience applying statistical methods (hypothesis testing, regression, predictive modeling) to data.

Mansioni

• Develop, train, and evaluate ML models to improve predictive performance for lending decisions.
• Analyze large datasets to identify patterns, develop features, and inform modeling approaches.
• Design and run experiments to test hypotheses and identify improvements.
• Collaborate with scientists and engineers to deploy models in production.
• Document methodologies and results to support reproducible workflows.

Conoscenze

Python

ML basics

Statistics

Hypothesis testing

Formazione

Bachelor’s degree in CS/Engineering/Math/Stats

Advanced degree (PhD) preferred

Strumenti

PyTorch

TensorFlow

scikit-learn

SQL

Descrizione del lavoro

Upstart is seeking an Applied Scientist to develop and evaluate machine learning models that improve lending decisions. You will work with scientists, engineers, and cross-functional partners to turn complex data into measurable improvements and scalable solutions.

You will analyze large datasets, design experiments, and help deploy models in production while documenting methodologies for reproducibility. A strong foundation in statistics and ML with Python is required, plus collaboration across