Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 9 days ago

Data Science Internship (Current PhD) - Summer 2027

Neighbor13 open roles

Where
Lehi, UT
Work mode
On site
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowData Science Internship (Current PhD) - Summer 2027Neighbor · Lehi, UT

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Neighbor's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

8.1% of postings close within 7 days. Measured by our own scanner across the market. Neighbor postings stay open a median of 19 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.6%3 days
  3. 8.1%7 days
  4. 15.1%14 days
  5. 34.0%30 days
This job: posted 9 days ago

Neighbor median: 19 days open

The 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 [email protected]. Check out our careers page to get to know us better as you think about your next step at Neighbor!

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Neighbor's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Neighbor's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Neighbor's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.