Instacart Data Scientist Interview Guide

If you’re preparing for the Data Scientist position at Instacart, here’s a detailed guide based on the experiences of candidates who have gone through the interview process. This information will help you navigate the process, covering everything from technical interviews to behavioral questions.

Interview Process Overview

1. Recruiter Screening:

Initial Call:

The process begins with an initial call from a recruiter, where they will assess your fit for the role, discuss your background in data science, and confirm your interest in Instacart. The recruiter may ask basic technical questions related to SQL, statistics, and data analysis.

• Example Question: “Can you describe a time when you used SQL to solve a complex data problem?”

The recruiter will also explain the job responsibilities, company culture, and next steps in the process.

2. Technical Interview (Data Analysis & SQL):

SQL and Data Manipulation:

The next round typically focuses on your ability to analyze data using SQL and other data science tools. You will be tested on your understanding of joins, window functions, and aggregations. Be prepared to solve queries on a live coding platform or in an interview-style environment.

• Example SQL Question: “Write a query to calculate the average order value per customer for the last quarter.”
• Example Data Analysis: “You have a dataset of user activity on the platform. How would you analyze the user’s buying behavior over time?”

You may also be asked to analyze and interpret datasets, demonstrating your ability to clean, process, and visualize data efficiently.

3. Product and Business Case Study:

Business Problem Analysis:

You’ll be asked to solve a business case study that involves analyzing product data and deriving actionable insights. These case studies test your ability to apply data science principles to real-world business problems and product strategy.

• Example Case: “Instacart is considering launching a new feature to reduce cart abandonment. How would you measure its impact on sales and user engagement?”

Key Points: Focus on how you would approach the problem with data, what metrics you would use, and how you would measure success. It’s important to demonstrate your strategic thinking and ability to prioritize business objectives.

4. Statistical Knowledge & Experimentation:

Expect questions on statistical methods, especially related to A/B testing, confidence intervals, p-values, and experiment design. Instacart is keen to assess your understanding of how to conduct and interpret experiments in a data-driven environment.

• Example Question: “Explain the difference between Type I and Type II errors in the context of A/B testing.”

Be ready to discuss sample size determination, statistical power, and how to handle confounding variables.

5. Behavioral Interview:

Collaboration and Communication:

The behavioral interview will assess your ability to work cross-functionally with teams like product, engineering, and marketing. Instacart values team-oriented candidates who can also communicate technical findings to non-technical stakeholders.

• Example Question: “Tell me about a time when you worked with a product team to deliver insights that influenced the product roadmap.”

Expect to discuss problem-solving in real-world scenarios, how you handle ambiguity, and your ability to meet deadlines in a fast-paced environment.

6. Final Round:

In the final round, you may meet with senior leaders or executives. This interview assesses your strategic alignment with Instacart’s goals, leadership skills, and ability to handle high-level business decisions.

• Example Question: “What data-driven strategies would you propose to improve customer retention on Instacart’s platform?”

Expect to explain how you would tackle complex business problems, prioritize initiatives, and collaborate with cross-functional teams.

Key Skills Instacart Looks For

1. SQL and Data Analysis:

You must have strong SQL skills, including knowledge of joins, aggregations, window functions, and subqueries. Instacart expects you to handle large datasets, perform data wrangling, and provide meaningful insights from the data.

• Example: “Write a SQL query to find the most frequently purchased items on Instacart.”

2. Statistics and Experimentation:

A solid understanding of statistical methods is essential, especially A/B testing, hypothesis testing, and the interpretation of p-values and confidence intervals. You should be comfortable designing and analyzing experiments to measure product impact.

• Example: “How do you determine the appropriate sample size for an A/B test?“

3. Machine Learning Knowledge:

While not always required, knowledge of machine learning algorithms (supervised and unsupervised learning), model evaluation, and feature engineering can be a plus. You may be asked about regression models, classification problems, and handling imbalanced datasets.

• Example Question: “How would you approach building a recommendation system for Instacart?“

4. Business Strategy:

Instacart seeks candidates who can translate data insights into actionable business strategies. Be prepared to discuss how you would apply data science to product development, user retention, and revenue growth.

• Example: “How would you approach analyzing user behavior to develop a strategy to increase repeat purchases?“

5. Cross-Functional Collaboration:

Collaboration with product, engineering, and other teams is key in this role. Instacart values data scientists who can work effectively with stakeholders to translate complex analyses into clear recommendations.

• Example Question: “Describe a time when you helped a product team implement a data-driven decision.”

Example Interview Questions

SQL:

• “Write a query to identify the customers who have not placed an order in the last 30 days.”
• “How would you calculate the average order value for customers in a given region?”

Business Case:

• “Instacart is considering offering a new discount program for first-time users. How would you measure its impact on user engagement and revenue?”
• “How would you evaluate the success of a new feature that allows users to track delivery times?”

Statistical Methods:

• “Explain the difference between Type I and Type II errors in hypothesis testing.”
• “What methods would you use to test the effectiveness of an A/B test for a new feature on Instacart?”

Behavioral:

• “Tell me about a time when you worked on a project with ambiguous requirements. How did you approach solving the problem?”
• “Describe a situation where you had to communicate a complex data insight to a non-technical audience.”

Tips for Preparation

1. Practice SQL:

Instacart places heavy emphasis on SQL skills. Practice writing complex queries to manipulate data and derive insights. Focus on joins, aggregations, window functions, and optimization techniques.

2. Understand Instacart’s Business:

Familiarize yourself with how Instacart operates, its customer base, and the challenges it faces. Be ready to apply data science to problems related to user engagement, product features, and business growth.

3. Prepare for Case Studies:

Practice solving product-focused business cases, structuring your answers clearly, and using data-driven insights to inform decisions.

4. Review Statistics and Experimentation:

Make sure you’re comfortable with A/B testing concepts, hypothesis testing, and interpreting experimental results. Brush up on statistical concepts like p-values, confidence intervals, and sample sizes.

5. Know Machine Learning Basics:

While not always required, it helps to have a good understanding of machine learning models and when to use them.