The University of Chicago Booth School of Business is a premier institution renowned for its rigorous curriculum and influential alumni network. Stepping into a Data Scientist position at Booth offers an unparalleled opportunity to merge academic prowess with practical application, immersing oneself in cutting-edge research and data analysis.

Joining Booth as a Data Scientist requires a solid foundation in statistics, machine learning, and data manipulation, coupled with the ability to extract meaningful insights from complex datasets. This role demands proficiency in coding and advanced analytical techniques to support decision-making processes and drive impactful research.

In this guide, we’ll navigate through the interview process, present commonly asked questions, and share invaluable tips to help you succeed. Ready to join one of the most prestigious business schools? Let's dive in!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining the University Of Chicago Booth School Of Business as a Data Scientist. Whether you were contacted by a Booth recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the University Of Chicago Booth School Of Business Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Booth data scientist hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Booth data scientist role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around the Booth's data systems, ETL pipelines, and SQL queries.

In the case of data scientist roles, take-home assignments regarding product metrics, analytics, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Booth office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the data scientist role at Booth.

Quick Tips For University Of Chicago Booth School Of Business Data Scientist Interviews

• Understand Booth's Core Research Focus: Research deeply into the specific areas of business and economics that Booth emphasizes. This will help you tailor your responses to align with their research goals.
• Showcase Analytical Skills: Booth focuses on analytical thinking and problem-solving. Prepare to discuss your past work in data science projects, emphasizing your analytical approach and decision-making process.
• Practice Behavioral Responses: University Of Chicago Booth values collaboration and intellectual curiosity. Prepare to answer behavioral questions that highlight your teamwork, adaptability, and eagerness to learn.

Typically, interviews at University Of Chicago Booth School Of Business vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• Write a function to find and return the last node of a singly linked list. You are given a singly linked list. Write a function to find and return the last node of the list. If the list is empty, return null.

• What metrics would you use to determine the value of each marketing channel for Mode? Given all the different marketing channels and their respective costs at Mode, a B2B analytics dashboard company, what metrics would you use to evaluate the value of each marketing channel?

• How would you measure the success of Facebook Groups? What criteria and metrics would you use to evaluate the success of Facebook Groups?

• What key parameters would you focus on improving to enhance customer experience on Uber Eats? To improve customer experience on Uber Eats, which key parameters would you prioritize for enhancement?

• How would you measure success for Facebook Stories? What metrics and criteria would you use to determine the success of Facebook Stories?

• What do you think are the most important metrics for WhatsApp? Which metrics do you consider most crucial for evaluating the performance and success of WhatsApp?

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of a logistic regression model when dealing with categorical and boolean variables.

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• What are the assumptions of linear regression? List and describe the key assumptions that must be met for linear regression to be valid.

• How would you tackle multicollinearity in multiple linear regression? Describe the methods you would use to identify and address multicollinearity in a multiple linear regression model.

• How would you encode a categorical variable with thousands of distinct values? Explain the techniques you would use to encode a categorical variable that has thousands of distinct values.

• How would you handle data preparation for building a machine learning model using imbalanced data? Describe the steps you would take to prepare data for a machine learning model when dealing with imbalanced datasets.

Embarking on your journey with the University of Chicago Booth School of Business as a Data Scientist could be your next career milestone. To sharpen your skills and increase your chances of success, head over to our main University Of Chicago Booth School Of Business Interview Guide, where we cover key interview questions and scenarios you might face. Dive into our expertly crafted guides for other positions to maximize your preparation.

At Interview Query, we're dedicated to empowering you with an extensive toolkit, offering the knowledge, confidence, and strategic guidance needed to master every aspect of your interview process. Explore our company interview guides for a more comprehensive preparation journey. If you have any questions, don't hesitate to reach out.

Best of luck with your interview!