Upstart is looking to expand access to credit using advanced machine learning models that better evaluate true risk.
Requirements
- Strong understanding of statistical, probability, and machine learning theory.
- Strong proficiency in SQL for querying and analyzing large datasets.
- Experience with Python and data analysis libraries.
- Knowledge of statistical methods for measuring uncertainty (e.g., Bayes, Frequentist approaches).
- Experience in building visualizations and maintaining Dashboards (Plotly or Matplotlib) to track model performance
- Experience with experimental testing, Causal Inference, A/B testing or Hypothesis testing
Responsibilities
- Build and refine metrics for model performance and help understand uncertainty around model performance.
- Conduct in-depth data analyses to uncover growth opportunities and inform pricing strategy.
- Collaborate with engineers and analysts to build scalable data pipelines that enable efficient data access.
- Partner with cross-functional teams to align on priorities and drive measurable business impact.
- Develop dashboards and reporting tools to monitor key metrics and track performance.
Other
- Advanced degree in Statistics, Mathematics, Economics, Finance, or a related quantitative field.
- 2+ years of experience in data science, analytics, or related fields.
- Strong critical thinking skills and ability to translate general problem statements into actionable solutions.
- Ability to translate complex data insights into business impact and strategic recommendations.
- Travel requirements: occasional in-person collaboration via regular onsite (once or twice per quarter for 2-4 consecutive days at a time).
- Time zone requirements: East/West coast time zones.
