Instacart Data Scientist Interview Guide

This guide will focus on interviewing for the senior level, but it also applies to other levels.

tl;dr

With a user base of over 85,000 stores, 1,500 retail banners, millions of shoppers, and over 185,000 shoppers, Instacart knows a thing or two about giving everyone a seat at the table. Data Scientists at Instacart support holistic company operations across  North America in revolutionizing how users and businesses put food on that table. Founded in 2012, Instacart takes a nourishing approach to retail enablement, with end-to-end retailer platforms for business growth and consumer apps that provide everything from everyday essentials to cosmetics and electronics.

Instacart’s interview processes are fairly standardized across the company, meaning that no matter the team you’re applying to join, you’ll likely see similar hiring structures, processes, and questions. Instacart interviewers prefer data science applicants with proficiency in:

• Experimentation
• A/B testing
• Metrics design
• Python
• SQL

What does an Instacart Senior Data Scientist do?

Instacart is continuously iterating on traditional models of grocery shopping, even recently acquiring Caper AI to help build smarter shopping carts (which makes LLM and machine learning experience a priority for many roles.) Instacart’s Data Scientists similarly bring blue-sky projects to fruition, innovating on how food gets from vendor to consumer. Data informs a wide spectrum of business decisions for Instacart, so Instacart Data Scientists’ models and experiments are vital to inform product decisions across all departments!

Data science hiring at Instacart is based on product area, not team, so you may get significant leeway to work on different projects within your product area, especially as you gain seniority. Instacart’s distributed workforce also makes hiring Senior Data Scientists with a proven track record in strong cross-team collaboration a priority for interviewers.

The average total compensation across data science levels at Instacart are:

• Data Scientist: $247K
• Senior Data Scientist: $365K
• Senior Staff Data Scientist 2: $411K

Before you apply

• Be ready to talk through a recent project stressing measurable business impacts
• Check out the Instacart tech blog to make sure you know about the latest initiatives
• Research the recent interview questions asked at Instacart
• Hone your Python skills since you will be assessed on them explicitly
• Check out the Exponent courses on hypothesis testing, power analysis and impact sizing, and experimentation to really ace your interviews!
• Grab a snack with the Instacart app at least a few times as an end user, so you can think about product needs
• Check out Instacart’s latest earnings statements. That way, when you’re in your experimentation and product case interviews, you can tie your answers to relevant company goals and metrics.

Interview process

Instacart is famous for its award-winning workplace culture, even rated by BuiltIn as one of the best workplaces of 2024. This makes their interview process highly competitive.

Unique within the industry, Instacart doesn’t have a dedicated “culture” or “values” interview—their recruiters assess candidates for culture-fit qualities like collaboration, communication, and agility throughout the interview process. Instacart likes to say that no matter what you bring to the potluck, there's a seat at the table for you.

Since hiring is based on product area, not team, candidates apply to an open-ended job description, and are placed on a team by the hiring manager only after passing their interviews. Applications become generally more role-specific as the interviews progress and as roles become more senior. Unlike tech companies of similar size, most candidates typically won’t meet with a hiring manager until after passing their onsite interviews. This is because Instacart prefers to put candidates through a standardized process before matching them with a team, similar to the hiring process at Google.

💡The questions in this guide are based on the experiences of data scientists interviewing for senior-level roles.

Instacart hiring loops tend to be fairly standardized. Interviewers generally describe three main interview stages for the interview loop at Instacart:

1. Recruiter phone screen to ensure you meet the minimum requirements for the role
2. Technical screens, which are generally split into two separate interviews
3. Onsite interviews, which are multi-hour and cover primarily technical topics

1. Recruiter phone screen

This call is intended to give the recruiter a sense of your work history and experience, and focuses more on logistics and behavioral questions than demonstrating complex technical skills. That said, the hiring manager may have passed along some skills or tools-based questions to ask you, since you likely won’t meet them until much later in the process.

Your recruiter will want to hear about your previous work history and skills as they relate to the job description and why you’re passionate about innovating in the field of grocery shopping, scalable data pipelines, mentorship, and machine learning (aka “why Instacart”).

Sample questions include:

• Walk me through your resume.
• Why Instacart?
• What are you looking for in your next role?
• Please share an instance when you and your manager disagreed.
• Tell me about a time you assisted one of your colleagues outside of your responsibilities. What happened, and how did it go?
• Tell me about a process or tool that you learned or developed at your previous job that you feel will be valuable in your future position at Instacart.
• How would you rank your Python skills on a scale of 1–10?
• What is your experience with A/B testing?

2. Technical interviews

Unique to Instacart, you’ll have two 45-minute online tech screens during the next phase of interviewing at Instacart. Instacart does this to ensure that only candidates who understand both statistics and SQL (in a product-case context) move forward.

In both tech interviews, your interviewer will be another Senior Data Scientist, evaluating you for communication and technical proficiency. The questions in both rounds will be more practical than theoretical, but you should still be ready for more binary “do you know X” questions about statistics concepts, especially as you interview for more senior roles.

Questions in the first technical screen will be on SQL and product-case topics, and the second will be more about statistics and experimentation.

a. SQL and product case screen

During this round, you’ll have 45 minutes to answer several SQL and product-case-related questions. Time will be split pretty evenly between the two main topics.

The SQL questions are typically scenario-based. You may be asked to generate a series of metrics given a scenario, and then asked to write SQL queries for these metrics.

The scenarios you’ll be given will likely be ones the company has recently worked through, so your interviewer will be looking for practical knowledge and judging you both on the metrics you design and the queries you use for them. Your interviewer will be looking for SQL queries that are correctly aligned to the metrics you’ve defined, even if they’re simple, so make sure you have the correct tool for the task.

According to interviewers, candidates at this stage often have difficulty generating SQL for both control and experiment groups, so be ready to flex your A/B testing experience if you have it.  Candidates without experimentation experience struggle through most of the Instacart Senior Data Scientist interview loop, but especially here.

Unique to Instacart, interviewers at this stage may ask you to incorporate ChatGPT into your queries. They’ll do this to see if you can write the correct prompts for it to generate correct SQL queries for your metrics, but they may also ask you to debug queries that have already been generated using ChatGPT.

Instacart Data Scientists are expected to use cutting-edge technology and tools while still maintaining critical thinking, and that balance between humans and LLMs is what’s being assessed here. Candidates who’ve had to do this have reported being “dinged” for not being independent enough, or relying too heavily on ChatGPT.

b. Statistics screen

This 45-minute screen will be primarily focused on statistics. You will be asked questions that feel like case studies from real-life experimentation at Instacart, similar to the previous screen, but in this one, you’ll be asked to think about tradeoffs between metrics, as well as risks.

Strong candidates remember to slow down and ask about the purpose of the experiment, and get other key company context before jumping in. Strong senior data science candidates can also discern when further experimentation is needed, and can recommend that versus trying to work with insufficient data.

Topics:

• SQL joins
• Simple SQL window functions (lag and lead)
• Simple SQL aggregation functions (group by, sum by)
• Hypothesis testing
• Experimentation
• P-value
• Type 1 and 2 errors
• Causal inference using observational data (for Senior and Staff Data Scientist roles only)

Sample questions include:

• Instacart’s gross merchandise volume (GMV) moved by a given percent this quarter. How would you investigate causes, and what recommendations would you make?
• Given a table with results from an experiment, what would you recommend to the product manager given these results? Are the p-values and tradeoffs statistically significant? How do you talk to PMs and other stakeholders to assess situations?

3. Onsite interviews

You’ll have four of these, typically back-to-back on the same day, designed to assess how you collaborate, communicate, and solve ambiguous problems. You’ll likely be invited for four hours in total, but some candidates have mentioned that some interviewers really want to dig down and take longer, especially in promising candidates. If they keep you into overtime, it’s generally a good sign. Some applicants were able to complete these over Zoom, but if you live near an Instacart office in NYC, San Francisco, or Toronto, you should expect to come in.

a. Experimentation round

This interview, typically an hour long, is designed to assess your comfort level with experimentation. Unlike the statistics-focused tech screen, which also asks about experimentation, the questions in this interview are typically more open-ended and entirely focused on scenarios. Your interviewer, a data scientist, will give you an organizational need, and you’ll walk them through all the steps in designing and analyzing the corresponding experiment, and the recommendations you’d make to the product team.

Topics:

• Randomization units in experimental design
• Network effects

b. Two separate product-case rounds

These two product-case rounds, typically an hour long each, will likely be more abstract and theoretical than the product-case questions you’ve already fielded in this interview loop. You may be asked to design an end-to-end feature based on a data set or need, and questions here are more open-ended than those you’ve seen previously.

This interview will also assess your collaboration skills with Instacart’s Product Team. Since Instacart Senior Data Scientists are expected to be involved in every aspect of the product life cycle, your ability to work with product team stakeholders is a key skill to emphasize here, though you may also be asked a few questions about experimentation.

Sample questions include:

• How and when would you incorporate data into the product life cycle? Why?
• When would you use a regression model, as opposed to an experiment, and why?

c. Take-home project review

A few days before your scheduled onsite date, you’ll be sent a prompt for your take-home project. Interviewers recommend that candidates use all available time, which is shorter than the take-home ramp-up time at companies like Spotify because Instacart’s prompts are typically more focused.

Much like your case studies, this prompt will require experimentation experience and typically be based on analyzing an experiment already running at Instacart. You’ll be given the experimental information and a series of questions based on the data.

You’ll have 45 minutes to present your findings at your onsite interview. These conversations are generally more informal than a traditional presentation, and many interviewers don’t even expect slides. They primarily want to see your Jupyter notebook and any other documentation you’ve created around your findings.

d. Leadership interview

Instacart recently added this hour-long conversation to their interview loops, and it’s similar to the Bar Raiser interview that software engineering candidates face in their hiring process, or a final interview at any other company. These conversations focus on gauging your leadership and project execution skills.

This interview will be your first with a hiring manager, who will ask you in detail about a past project. Your interviewer will want to know:

• How and when you’ve gone above and beyond, and the technical and business impact it had on your company as a whole
• Details about the complex issues of the project, and how you resolved them

Make sure you’re providing numerical details at every step, and that you’re able to slow down and speak about various points in the project lifecycle, including post-launch, during the project, managing collaboration, and facing technical challenges.

During this interview, you’ll also be asked about how you collaborate. While this may sound like simple behavioral questions, Instacart sees collaboration as a skill with measurable business impact, so you should, too. Hiring managers at Instacart assess your collaboration skills in three areas:

1. How you’ve collaborated through past areas of conflict
2. How you’ve led projects to meaningful business impacts
3. How you mentor other developers to measurable success

Candidates who get offers from Instacart can speak clearly on all three during their leadership interview.

Common follow-up questions at this stage are often “What could have been better?” and “What did you learn?” A project where you have room to reflect and show strategy will make a better impression here than a project where everything went perfectly the first time. Great leadership interview candidates show they’re thinking of the future of the project, not just current wins, and demonstrating long-term thinking.

Sample questions include:

• Tell us about a recent project from your resume. Can you take us through the process of how you delivered it from start to finish?
• What's your approach to cross-functional collaboration?
• Name a time when you had to make a product decision, but stakeholders wanted different things. What did you do?
• Tell me about a difficult problem you solved with a simple solution.
• Can you talk about a product launch you worked on? What was your involvement, and what was the end result?

Additional resources

• Take our course to level up your data science skills.
• Get coaching and actionable feedback from data scientists at the level you aspire to land an offer for.
• Practice with mock interviews on the most common types of problems.

FAQs about the Instacart Senior Data Scientist interview

What can I expect from my interview at Instacart?

For your senior data scientist interview at Instacart, you can expect three main phases (recruiter, technical screens, onsite) that assess your skills with statistics, experimentation, product life cycle, and Python and SQL, and reflect on past projects with an eye for future iteration and business improvements.

On average, how much do Instacart Data Scientists typically make?

The average total compensation across data science levels at Instacart are:

• Data Scientist: $247K
• Senior Data Scientist: $365K
• Senior Staff Data Scientist 2: $411K

How long is the typical Instacart interview process?

Typically, interview loops at Instacart take 4–6 weeks, but popular or senior-level roles may see delays.

How should I prepare for a Senior Data Scientist interview at Instacart?

• Be ready to talk through a recent project stressing measurable business impacts
• Check out the Instacart tech blog to make sure you know about their latest projects
• Research the recent interview questions asked at Instacart
• Make sure you’re proficient in Python and SQL
• Try out the Instacart platform so you can speak to features (and grab a snack!)
• Check out Instacart’s latest earnings statements. That way, when you’re in your experimentation and product case interviews, you can tie your answers to relevant company goals and metrics.

Will I have in-person interviews at Instacart?

Instacart is a flex-first workplace, so if you live near one of the three main office locations in San Francisco, New York, or Toronto, you’ll likely interview in person, but may have flexibility about where you work if you get the job.