Data Science Internship (Current PhD) - Summer 2027

Neighbor•Lehi, UT

About The Position

Neighbor is seeking a Data Scientist Intern to join their Data & Analytics team for Summer 2027. This role involves working on existing machine learning models in production, such as lifetime value, unit economics, and forecasting, to improve their accuracy. The intern will also assist Product, Marketing, and Sales divisions with designing A/B tests and interpreting their results. The work directly influences decisions within a marketplace operating in nearly every U.S. city. This internship is ideal for a PhD student looking to apply research skills to real business challenges. The intern will report to the Data & Analytics manager and receive regular code review and hands-on mentorship. The technology stack includes Python, dbt, and Dagster on Redshift and Athena, with a Cube semantic layer and Superset for BI.

Requirements

Currently enrolled PhD-level candidate in a quantitative field (Computer Science, Statistics, Math, Physics, Data Science, etc.) with completion expected by May 2028; transcript required.
Demonstrated research, coursework, or project experience applying statistics and machine learning to real-world or complex datasets.
Strong SQL and fluent Python for modeling.
Academic or project-based experience with A/B testing design or statistical hypothesis testing.
Solid understanding of inference, including explaining confidence intervals, the impact of adding metrics on p-values, leakage in validation splits, and data limitations.
Strong problem-solving mindset and eagerness to diagnose and improve existing code and statistical models.
Intellectual persistence to investigate discrepancies and ensure belief in explanations before shipping.
Clear communication skills with non-technical stakeholders, explaining results and uncertainty without jargon or overclaiming.

Nice To Haves

Experience with dbt or semantic layers like Cube.

Responsibilities

Improve lifetime value and unit economics models by retraining, re-engineering features, and validating predictions.
Audit inherited models to identify issues like leakage, stale assumptions, performance degradation in specific segments, and ineffective features.
Build forecasts for operators, including demand and supply by market, revenue, and influencing factors.
Partner with Product, Marketing, and Sales to design A/B tests before launch.
Analyze test results and provide clear conclusions about what designs can and cannot identify.
Become a subject matter expert on Neighbor's product, users, and marketing lifecycle.