Back to jobs

Data Science Internship (Current PhD) - Summer 2027

Pay
Pay not listedSimilar roles state $118K–$193K
Work setting
On-site — work setting source
Work setup in the employer’s posting: onsite
From the employer’s posting
Employment
Internship — employment source
Employment type in the employer’s posting: Intern
From the employer’s posting

Before you apply

New graduates
For current studentsJob title: Data Science Internship (Current PhD) - Summer 2027

What you’ll work on

Full posting
  • Retrain and re-engineer lifetime value and unit economics models, validating against realized outcomes

  • Audit inherited models for leakage, stale assumptions and segments where performance fails

  • Build demand, supply and revenue forecasts by market that operators can plan against

  • Help Product, Marketing and Sales design A/B tests and review them for power before launch

  • Analyze test results, make a recommendation and state what each design can and cannot show

From the employer’s posting
Improve our lifetime value and unit economics models. Retrain them, re-engineer their features, and validate their predictions against realized outcomes.
Audit inherited models: find the leakage, the stale hardcoded assumption, the segment where performance quietly falls apart
Build forecasts our operators actually plan against: demand and supply by market, revenue, and the levers that move them.
Partner with Product, Marketing, and Sales to design tests before they launch.
Analyze results and make a call and be candid about what each design can and can't identify

What you’ll bring

All qualifications

Core experience

  • Strong SQL and fluent Python for modeling are required; experience with dbt or semantic layers like Cube is a big plus, but we're happy to train you on our specific transformation stack
Qualification wording
Strong SQL and fluent Python for modeling are required; experience with dbt or semantic layers like Cube is a big plus, but we're happy to train you on our specific transformation stack
Education & alternatives
At Neighbor, we’re building the largest hyperlocal marketplace the world has ever seen. We’ve raised over $75 million from top-tier investors such as Andreessen Horowitz and the CEOs of DoorDash, StockX, and Uber. Our marketplace is already flourishing in all 50 states and we’re just getting started! We're excited to add a Data Scientist Intern to our Data & Analytics team. You'll work on the machine learning models we already run in production, including lifetime value, unit economics, and forecasting, making them more accurate and showing with evidence that they've improved. You'll also help Product, Marketing, and Sales divisions design A/B tests and interpret the results. Your work feeds directly into decisions across a marketplace that operates in nearly every U.S. city. This is a great fit for a PhD student who wants to apply their research skills to live business problems. You'll report to our Data & Analytics manager, with regular code review and hands-on mentorship. Our stack: Python, dbt, and Dagster on Redshift and Athena, with a Cube semantic layer and Superset for BI.
Qualifications - PhD-level candidate currently enrolled in a quantitative field (Computer Science, Statistics, Math, Physics, Data Science, etc.) completing your PhD by May of 2028; transcript required - Demonstrated research, coursework, or project experience applying statistics and machine learning to real-world or complex datasets

About Neighbor

Neighbor is the largest and most comprehensive marketplace for self storage and parking, with listings in almost every U.S. city.

In the employer’s words · Read in context

Apply at Neighbor

Posting record

Report an error
Status in our records
Live
First seen by us
Sep 29, 202636 days ago
Recorded sightings
23
Last seen by us
Nov 3, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 36

Similar jobs usually come down between day 7 and day 55.

From 9,988 similar postings that came down. Coming down is not always a hire.

Neighbor is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • dbt
  • Redshift
  • Superset
  • Dagster
Where the posting names them
We're excited to add a Data Scientist Intern to our Data & Analytics team. You'll work on the machine learning models we already run in production, including lifetime value, unit economics, and forecasting, making them more accurate and showing with evidence that they've improved. You'll also help Product, Marketing, and Sales divisions design A/B tests and interpret the results. Your work feeds directly into decisions across a marketplace that operates in nearly every U.S. city. This is a great fit for a PhD student who wants to apply their research skills to live business problems. You'll report to our Data & Analytics manager, with regular code review and hands-on mentorship. Our stack: Python, dbt, and Dagster on Redshift and Athena, with a Cube semantic layer and Superset for BI. The Problems You'll Solve
- Demonstrated research, coursework, or project experience applying statistics and machine learning to real-world or complex datasets - Strong SQL and fluent Python for modeling are required; experience with dbt or semantic layers like Cube is a big plus, but we're happy to train you on our specific transformation stack - Academic or project-based experience with A/B testing design or statistical hypothesis testing

Your next step

Complete your application on jobs.lever.co. The employer’s form will show what is required.

Applying through Lever

  • No account needed: one form, and Lever reads your resume into the profile recruiters search.

Already applied? Track this application

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

At Neighbor, we’re building the largest hyperlocal marketplace the world has ever seen. We’ve raised over $75 million from top-tier investors such as Andreessen Horowitz and the CEOs of DoorDash, StockX, and Uber. Our marketplace is already flourishing in all 50 states and we’re just getting started!

We're excited to add a Data Scientist Intern to our Data & Analytics team. You'll work on the machine learning models we already run in production, including lifetime value, unit economics, and forecasting, making them more accurate and showing with evidence that they've improved. You'll also help Product, Marketing, and Sales divisions design A/B tests and interpret the results. Your work feeds directly into decisions across a marketplace that operates in nearly every U.S. city. This is a great fit for a PhD student who wants to apply their research skills to live business problems. You'll report to our Data & Analytics manager, with regular code review and hands-on mentorship.

Our stack: Python, dbt, and Dagster on Redshift and Athena, with a Cube semantic layer and Superset for BI.

The Problems You'll Solve

  • Improve our lifetime value and unit economics models. Retrain them, re-engineer their features, and validate their predictions against realized outcomes.
  • Audit inherited models: find the leakage, the stale hardcoded assumption, the segment where performance quietly falls apart, and the feature that's doing less work than everyone believes.
  • Build forecasts our operators actually plan against: demand and supply by market, revenue, and the levers that move them.
  • Partner with Product, Marketing, and Sales to design tests before they launch. Catching an underpowered test in the design review is worth more than any analysis you can do afterward.
  • Analyze results and make a call and be candid about what each design can and can't identify
  • Become a subject matter expert on Neighbor's product, users, and marketing life cycle. The modeling is the easy part; knowing which features mean something is the hard part.

Qualifications

  • PhD-level candidate currently enrolled  in a quantitative field (Computer Science, Statistics, Math, Physics, Data Science, etc.) completing your PhD by May of 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 are required; experience with dbt or semantic layers like Cube is a big plus, but we're happy to train you on our specific transformation stack
  • Academic or project-based experience with A/B testing design or statistical hypothesis testing
  • Real grounding in inference, not just fitting: you can explain what your confidence interval means, why the p-value moved when you added a second metric, how leakage sneaks into a validation split, and when you don't have the data to answer the question
  • Strong problem-solving mindset and eagerness to diagnose and improve existing code and statistical models
  • Intellectual stubbornness in a productive direction: you keep pulling on a thread when the numbers don't reconcile, and you don't ship an explanation you don't believe
  • Clear communication with non-technical stakeholders: you can explain a result and its uncertainty without either overclaiming or hiding behind jargon
About Neighbor:
Neighbor is the largest and most comprehensive marketplace for self storage and parking, with listings in almost every U.S. city. From storage facilities to neighborhood garages, driveways, and RV spots, Neighbor brings every option together in one simple search. Come help us disrupt the $500 billion storage and parking industry! This is a unique opportunity to join a fast-growing, VC-backed tech startup. You will be part of a an extremely talented, hardworking and passionate team committed to changing the world one neighbor at a time.
 
Neighbor is an equal opportunity employer and is committed to providing a positive interview experience for every candidate. If accommodations due to a disability or medical condition are needed, connect with us via email at hr@neighbor.com. Check out our careers page to get to know us better as you think about your next step at Neighbor!

Employment type

Intern

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Lehi, UT

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.