Applied Scientist Intern
About this role
Conduct offline analyses, perform self-directed investigations, and present findings to the machine learning team while receiving mentorship from experienced practitioners. Research and design machine learning models and technical enhancements to improve the lending marketplace platform that handles millions of predictions using thousands of signals.
Created for quantitative students on track to graduate by 2028, this internship provides an opportunity to apply statistical and machine learning theory to real-world financial products. Individuals who succeed in this position demonstrate intellectual curiosity, strong communication skills, and the ability to use modern agentic tooling efficiently.
What you will do
- Research machine learning and statistical approaches to discover improvements to predictive performance and business value.
- Design, implement, and evaluate model, product, or technical enhancements using rigorous experimentation and validation methods.
- Translate research findings into clear recommendations, documented methodologies, and production-ready solutions.
- Work with mentors to align stakeholders and drive next steps.
- Identify potential problems or opportunities for improvement in the codebase and suggest solutions through self-directed investigation.
What you need
- Currently enrolled in a Bachelor's, Master's, or PhD degree program in mathematics, statistics, physics, econometrics, computer science, or a related quantitative field.
- On track to graduate by 2028.
- Demonstrate strong fundamentals in statistical, probability, and machine learning theory.
- Ability to perform data analysis and evaluate machine learning or statistical models using Python.
- Possess basic SQL foundations along with the ability to use modern agentic tooling efficiently.
- Exhibit intellectual curiosity, humility, drive, teamwork, and strong communication skills.
Nice to have
- PhD in mathematics, statistics, physics, econometrics, computer science, or a related quantitative field
- On track to graduate by the summer of 2028
- Experience in supervised learning, model evaluation, and feature engineering techniques
- Advanced statistical, frequentist, Bayesian, causal theory, or econometrics knowledge
- Strong coding skills in Python
Benefits
- Competitive compensation including base pay, bonus opportunities, and annual equity grants
- Retirement benefits including a 401(k) with a company match
- Comprehensive health coverage including medical, dental, vision, and wellness resources
- Income protection benefits including life insurance and disability coverage
- Paid time off, sick leave, and company holidays
- Annual wellness and productivity allowances
Skills and tech stack
Questions candidates ask
What is the remote work policy for this role?
The role is fully remote as part of a digital-first company where employees can live and work anywhere in the U.S. Over the course of the internship, you will meet to collaborate once or twice for two to four consecutive days at a time.
What is the anticipated salary range for this position?
The anticipated base salary for this position is expected to be within the range of $141,000 to $150,000 USD. Your actual base pay will depend on your geographic location, job-related skills, experience, and relevant education.
What qualifications are required regarding graduation timeline?
Candidates must be pursuing a degree in mathematics, statistics, physics, econometrics, computer science, or a related quantitative field and be on track to graduate by 2028.
What tools and technologies will I need to use?
You will need the ability to perform data analysis and evaluate models using Python, possess basic SQL foundations, and know how to use modern agentic tooling such as Claude Code and Codex efficiently.