Upstart
Applied Scientist
$142K–$196K
United States +2 · Remote · Full-time · Posted Oct 28, 2026
- Location
- United States
Remote
Remote - Experience
- 2+ years; academic or industry setting.
- Education
- Graduate degree in mathematics, applied mathematics, statistics, physics, econometrics, operations research, computer science, or a related quantitative field.
About the job
Use causal inference, experimentation, and machine learning to optimize customer offers and build production-ready offer-selection models and decision strategies.
What you'll do
- Develop causal machine-learning models and production-ready offer-selection code.
- Design experiments and measure offer changes using statistically rigorous methods.
- Translate findings into recommendations and collaborate with business, product, engineering, machine-learning, and model-risk partners.
What they ask for
- Graduate degree in a quantitative field or a related field.
- 2+ years conducting machine-learning, statistical-modeling, or applied quantitative research in academia or industry.
- Experience applying causal inference and experimentation to real-world decisions.
- Expertise in applied statistics, probability, and experimental design; production-quality Python coding experience.
Nice to have
- PhD in a quantitative field.
- Experience with marketplace optimization, causal machine learning or treatment-effect modeling, or taking research through production-model development.
Pay
$141,500 — $196,000 USD (base salary)
Tools
Python
AI focus
Apply causal machine learning and experimentation to optimize customer offers and conversion; develop production-ready models and decision strategies.
Model-written summary · the original posting is authoritative