Remote Applied Scientist — ML for Smarter Lending

OhioX; Columbus, Austin, San Francisco, New York (OH, TX, CA, NY); Ibrido; USD 142.000 - 196.000; Tempo pieno

Descrizione del lavoro

Upstart is seeking an Applied Scientist to develop and evaluate machine learning models that address meaningful business problems. You will collaborate with scientists, engineers, and cross-functional partners to translate complex data into modeling improvements and measurable outcomes.

You should have a Bachelor's in a relevant field, 0–2 years ML experience, Python proficiency, and familiarity with ML frameworks.

Competenze

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

Mansioni

• Develop, train, and evaluate machine learning models to improve predictive performance and inform lending decisions.
• Analyze large datasets to identify patterns and features for modeling improvements.
• Design and run experiments to validate hypotheses and identify opportunities for improvement.
• Collaborate with scientists and engineers to deploy and monitor models in production.

Conoscenze

Machine Learning

Python

Statistics

Experiment design

Formazione

Bachelor's degree in CS/Engineering/Math/Statistics

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 address meaningful business problems. You will collaborate with scientists, engineers, and cross-functional partners to translate complex data into modeling improvements and measurable outcomes.

You should have a Bachelor's in a relevant field, 0–2 years ML experience, Python proficiency, and familiarity with ML frameworks.