Applied Scientist Intern

Upstart

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$141,000–$150,000 / yr
Employment
Intern
Posted
12 days ago
Freshness
Confirmed live yesterday
Closes
Dec 28, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $177k
This role $146k
$99k most similar roles pay here $258k

This role pays less than 66% of similar roles. Most pay $114,400–$238,878 — the shaded band above. At the midpoint, this role pays about $146k versus about $177k for comparable roles.

Based on 240 similar postings.

Employer

About Upstart

Upstart is an AI lending platform that partners with banks and credit unions to expand access to affordable credit using non-traditional variables.

Upstart currently has 46 open roles on FindRole.

Listed pay typically runs $166,900–$230,000 across 45 roles with salary data.

Most-posted roles

View all roles at Upstart

At a glance

TL;DR · Applied Scientist Intern

As an Applied Scientist Intern, you will join a team focused on improving predictive performance and business value through machine learning and statistical research. You will identify opportunities for improvement, conduct self-directed investigations, perform offline analyses, and present findings to the machine learning team. Your daily work involves designing, implementing, and evaluating model enhancements using rigorous experimentation and validation methods while translating complex research into production-ready solutions. To succeed in this role, you must possess strong fundamentals in statistical, probability, and machine learning theory. You will utilize Python for data analysis and evaluation, apply basic SQL foundations, and leverage modern agentic tooling like Claude Code or Codex. The work centers on the lending marketplace domain, specifically utilizing advanced AI to improve credit decisioning by analyzing numerous signals to provide smarter outcomes for borrowers.

What does a Applied Scientist earn?

Median $231000 from 41 postings across 11 companies.

See salary data

What you'll do

  • Research machine learning and statistical approaches to improve model predictive performance and business value.
  • Design, implement, and evaluate model, product, or technical enhancements using rigorous experimentation.
  • Translate research findings into clear recommendations and documented methodologies for the team.
  • Develop production-ready solutions based on offline analyses and creative problem-solving.
  • Identify potential problems or opportunities within the codebase and suggest actionable improvements.
  • Perform data analysis and evaluate machine learning models using Python and SQL.
  • Utilize modern agentic tooling to improve development efficiency and output.

What we're looking for

  • Bachelor, Master, or PhD degree in mathematics, statistics, physics, econometrics, computer science, or a related quantitative field.
  • On track to graduate by 2028.
  • Strong fundamentals in statistical, probability, and machine learning theory.
  • Ability to perform data analysis and evaluate models using Python and basic SQL foundations.
  • Ability to use modern agentic tooling like Claude Code or Codex efficiently.
  • Strong communication skills, intellectual curiosity, humility, drive, and teamwork.
  • Experience in supervised learning, model evaluation, and feature engineering techniques (preferred).
  • Advanced statistical theory including frequentist, Bayesian, causal, or econometrics knowledge (preferred).

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