Senior Applied Scientist — Remote ML Innovator

OhioX; Stati Uniti; Remoto; USD 168.000 - 232.000; Tempo pieno

Descrizione del lavoro

Upstart is seeking a Senior Applied Scientist to lead ML solutions that improve model performance and business outcomes. You will own complex modeling problems from investigation through production, shaping technical approaches and best practices with engineering and product partners.

You’ll design advanced modeling methods, evaluate experiments, and translate complex requirements into measurable ML objectives to deliver reliable, scalable results across platforms and geographies.

Competenze

• Bachelor’s degree in CS, engineering, math, statistics, or related field.
• 3 years of experience developing/evaluating ML models or applying statistical methods.
• Experience with Python and established ML frameworks.
• Experience designing and evaluating experiments using statistical methods.
• Experience implementing, deploying, or maintaining ML models in production environments.

Mansioni

• Lead end-to-end development of ML models from problem formulation to deployment and evaluation.
• Design and evaluate advanced modeling approaches to improve accuracy, robustness, and effectiveness.
• Identify opportunities to improve models through feature development and rigorous analysis.
• Partner with engineering, product, and business stakeholders to translate requirements into measurable ML objectives.
• Guide technical decisions and share methodologies to improve team impact.

Conoscenze

Machine Learning

Python

Experimentation

Statistical Analysis

Production Deployment

Formazione

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

Strumenti

ML frameworks (Python)

Descrizione del lavoro

Upstart is seeking a Senior Applied Scientist to lead ML solutions that improve model performance and business outcomes. You will own complex modeling problems from investigation through production, shaping technical approaches and best practices with engineering and product partners.

You’ll design advanced modeling methods, evaluate experiments, and translate complex requirements into measurable ML objectives to deliver reliable, scalable results across platforms and geographies.