Applied Scientist

Upstart

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Canada
Salary
$141,500–$196,000 / yr
Posted
100 days ago
Freshness
Confirmed live yesterday
Closes
Dec 8, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $190k
This role $169k
$119k most similar roles pay here $251k

This role pays less than 56% of similar roles. Most pay $142,405–$238,287 — the shaded band above. At the midpoint, this role pays about $169k versus about $190k 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 73 open roles on FindRole.

Listed pay typically runs $166,900–$230,450 across 72 roles with salary data.

Most-posted roles

View all roles at Upstart

At a glance

TL;DR · Applied Scientist

As an Applied Scientist on the Machine Learning Growth team, you will develop and improve models to optimize borrower acquisition across various marketing channels including direct mail, email, and digital platforms. You will perform business-oriented analysis, conduct machine learning research, design statistically rigorous experiments to measure causal impact, and build reusable data pipelines from complex datasets. The role involves collaborating with Machine Learning and Marketing Platform Engineering stakeholders to translate business problems into production-ready solutions for products like Personal Loans and Home Equity Lines of Credit. To succeed, you must possess a Master’s or PhD in a quantitative field such as Mathematics, Statistics, or Economics. Required skills include proficiency in Python for data preparation and model development, along with expertise in causal inference, experimental design, and advanced machine learning techniques to enhance marketing outcomes.

What does a Applied Scientist earn?

Median $208800 from 47 postings across 10 companies.

See salary data

What you'll do

  • Analyze historical model and campaign performance to identify opportunities for improving marketing outcomes.
  • Develop and evaluate machine learning models by researching new features and architectures to improve prospect selection.
  • Design statistically rigorous experiments and evaluations to measure causal impact and optimize campaign results.
  • Build reusable data pipelines, metrics, and analytical approaches to navigate complex datasets.
  • Translate business problems into research agendas and production-ready solutions with engineering and growth teams.
  • Expand machine learning capabilities across various marketing channels including email, digital, and lifecycle marketing.

What we're looking for

  • Master’s Degree in Mathematics, Statistics, Economics, Operations Research, or a related field.
  • PhD in Mathematics, Statistics, Economics, Operations Research, or a related field (preferred).
  • Experience applying statistical and machine learning methods to modeling or data science problems.
  • Experience using Python for data analysis, data preparation, and machine learning model development.
  • Experience with causal inference and experimental design, including statistically rigorous evaluation of performance.
  • Knowledge of causal machine learning methods and modeling approaches (preferred).
  • Ability to translate broadly scoped business problems into structured research questions, analyses, and modeling approaches (preferred).
  • Experience working across exploratory data analysis, machine learning research, experimentation, and production model development (preferred).

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