ML Researcher – Underwriting & Finance (On-site SF)

Rise Talent Advisors; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Equity

Job summary

Rise Talent Advisors is helping a venture-backed company in San Francisco hire a machine learning researcher to work on-site five days a week. You will build predictive models for underwriting and financing decisions using traditional ML and deep learning on large, real-world datasets that impact real financing decisions.

The role is about 70 percent research and 30 percent production. You will design the research plan, perform rigorous evaluations with temporal validation and leakage checks,

Qualifications

• 5 to 12 years of machine learning research experience.
• Master’s or PhD in computer science, math, physics, or a quantitative field.
• Experience building predictive models with traditional ML and deep learning.
• Rigorous evaluation habits and production deployment experience.

Responsibilities

• Build predictive models for underwriting and financing using ML and DL.
• Work with large real-world datasets and enforce strict evaluation (temporal validation, calibration, leakage checks).
• Perform feature engineering and interpretability work with SQL, Pandas/Polars, SHAP.
• Design the research plan: questions, holdout, metrics, success criteria.
• Put models into production and monitor drift after launch.
• Split time between research and production to ensure robust models.
• Explain model behavior and limits to partners who use results for decisions.

Skills

ML Research

Deep Learning

Predictive Modeling

Model Evaluation

Production ML

Data Analysis

Education

MSc/PhD in CS/Math/Physics or quantitative field

Tools

SQL

Pandas/Polars

SHAP

Job description

Rise Talent Advisors is helping a venture-backed company in San Francisco hire a machine learning researcher to work on-site five days a week. You will build predictive models for underwriting and financing decisions using traditional ML and deep learning on large, real-world datasets that impact real financing decisions.

The role is about 70 percent research and 30 percent production. You will design the research plan, perform rigorous evaluations with temporal validation and leakage checks,