The Team:

Upstart’s ML verifications team seeks to efficiently mitigate excess risk by identifying potentially fraudulent or dishonest applicants and verifying their information. We build, maintain, and iteratively improve upon a suite of ML models and own the logic for how they are used to make operational decisions. We significantly and directly impact business performance and are

As a Research Scientist on ML verifications at Upstart, you will improve conversion rates and reduce excess losses by researching and implementing new features and models to accurately detect and mitigate risk. You will collaborate with product, engineering, and other scientists and communicate your approach and results to both technical and non-technical audiences, and contribute positively to the team’s culture.

How you’ll make an impact

Independently execute ML modeling and feature research projects Develop and socialize approaches in collaboration with other scientists and cross-functional stakeholdersWrite clean, readable code to execute reproducible analyses Communicate and socialize findings to get buy in for recommended next stepsImplement models for production

Minimum Qualifications

• Strong academic credentials with a master's degree in statistics, mathematics, economics, computer science, or other quantitative areas of study
• Programming skills in Python
• Proficiency in a broad array of mathematical, statistical learning and machine learning concepts and applications
• Ability to proactively and effectively communicate results and methodologies to both technical and non-technical stakeholders
• Strong sense of intellectual curiosity balanced with humility, drive and teamwork

Preferred Qualifications

• PhD in in statistics, mathematics, economics, computer science, or other quantitative areas of study
• Full-stack expertise with all steps of the modeling process from ideation to productionalizing code; OR deep expertise in either statistical modeling or machine learning
• Knowledge of MLops, pipelines, and engineering architecture
• Experience solving real-world machine learning problems at a tech company, such as through internships
• Experience working as part of a diverse, cross-functional team.

Position location This role is available in the following locations: Remote

Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions’ cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.

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