Huron Consulting Group is a leading management consulting firm that specializes in navigating today’s complex business challenges. They offer expertise in healthcare, higher education, and life sciences, providing innovative solutions to transform client operations and drive growth.

Data Scientists at Huron Consulting play a pivotal role in harnessing data-driven insights to solve intricate client problems. This position requires strong skills in machine learning, statistical analysis, and data visualization. Additionally, collaboration with cross-functional teams to design and implement advanced analytical models is imperative.

If you aspire to join the innovative team at Huron Consulting Group, this guide by Interview Query is tailored for you. We’ll navigate through the interview process, review essential Data Scientist interview questions, and share expert tips to help you succeed. Let’s dive in!

Submitting Your Application

The first step is to submit a compelling application that reflects your proficiency in data science and your enthusiasm for joining Huron Consulting Group. Whether you were contacted by a recruiter from Huron or you're initiating your application on your own, examine the job description thoroughly and tailor your CV accordingly.

Tailoring your CV should include identifying specific keywords that align with the job requirements and crafting a focused cover letter. Ensure to highlight relevant skills and detailed descriptions of your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV is shortlisted, a recruiter from Huron's Talent Acquisition Team will contact you to verify your professional experience and technical skills. Behavioral questions may also be part of this initial screening.

In some scenarios, the hiring manager might join the call to answer questions regarding the role and the company, and might also delve into preliminary technical and behavioral discussions.

This call typically lasts about 30 minutes.

Technical Virtual Interview

Once you pass the recruiter screening, you will be invited for a technical virtual interview. This stage generally involves a video conference where you may be required to share your screen. The interview lasts about an hour and you should be prepared to discuss ETL pipelines, SQL queries, and specific data systems used at Huron Consulting Group.

For data scientist roles, take-home assignments involving data analysis, visualization, and machine learning models may be provided. Your understanding of statistical principles, probability distributions, and other data science fundamentals will be evaluated during this interview.

Depending on the seniority of the position, you may also be tasked with solving case studies or other real-world scenario-based problems.

Onsite Interview Rounds

After a successful technical virtual interview, another call will outline the next steps, which include the onsite interview. During this stage, multiple rounds of interviews will be conducted at Huron's offices, with each round focusing on different aspects of your technical and analytical skills.

You may undergo a diverse range of interviews, including coding challenges, machine learning model discussions, and statistical problem-solving. If you previously completed a take-home assignment, you may need to present your findings during an onsite meeting.

Quick Tips For Huron Consulting Group Data Scientist Interviews

• Research Their Methodologies: Huron Consulting Group deals with various industries and consults on different business problems. Make sure to understand common methodologies they might use and be prepared to discuss them.
• Be Client-Centric: Given the consulting nature of Huron's business, exhibit your ability to communicate technical findings to non-technical stakeholders effectively. Strong communication skills can set you apart.
• Polish Up on Tools and Techniques: Brush up on your familiarity with key tools such as SQL, R, Python, and ML algorithms. Practical examples where you've applied these tools successfully will help you stand out.

Typically, interviews at Huron Consulting Group vary by role and team, but commonly Data Scientist interviews follow a fairly standardized process across these question topics.

• How would you set up an A/B test for button color and position changes? A team wants to A/B test multiple changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you set up this test?

• How would you forecast Facebook's revenue for the next year? You work on the revenue forecasting team at a company like Facebook. An executive asks you to forecast the company's revenue for the coming year. How would you approach this task?

• How would you determine if an email campaign redesign led to increased conversion rates? An E-commerce store's new marketing manager redesigned the new-user email journey, and the conversion rate increased from 40% to 43%. However, the rate was 45% a few months prior. How would you investigate if the redesign caused the increase, rather than other factors?

• How would you ensure data quality across multiple ETL platforms for PayPal's market research? PayPal partnered with a local survey platform for market research in Southern Africa. The data includes pre-quantified and text data in different languages, stored within each country's borders. How would you ensure data quality across the ETL pipelines connecting PayPal’s data marts with the survey platform’s data warehouses?

• How would you conduct an experiment to test Uber's new ETA range feature? A PM at Uber is considering a new feature that displays an ETA range (e.g., 3-7 minutes) instead of a direct estimate (e.g., 5 minutes). How would you conduct this experiment and determine if the results are significant?

• Write a function min_distance to calculate the minimum absolute distance between two elements in an array and return all pairs with that difference. Given an array of integers, write a function min_distance to calculate the minimum absolute distance between two elements and return all pairs having that absolute difference. Ensure the pairs are returned in ascending order.

• Write a query to select the top five most expensive projects by budget to employee count ratio, accounting for duplicate rows in the employee_projects table. We have two tables: projects and employee_projects. Write a query to select the five most expensive projects by budget to employee count ratio, considering the existence of duplicate rows in the employee_projects table.

• Write a function to simulate drawing balls from a jar. Given a list jar with ball colors and a corresponding list n_balls with counts, write a function to simulate drawing a ball from the jar.

• Design three classes: text_editor, moving_text_editor, and smart_text_editor with specific functionalities. Design three classes: text_editor, moving_text_editor, and smart_text_editor. Each class should have specific methods and functionalities as defined.

• Write a query to determine the top 5 actions performed during Thanksgiving week and rank them. Write a query to determine the top 5 actions performed during the week of Thanksgiving (11/22/2020 - 11/28/2020) and rank them based on the number of times performed. Include the action and their rank in ascending order.

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to a non-technical person, focusing on its role in determining the significance of results in hypothesis testing.

• What is the probability that it's actually raining in Seattle given your friends' responses? You called 3 friends in Seattle to ask if it's raining. Each has a 2/3 chance of telling the truth and a 1/3 chance of lying. All 3 said "Yes." Calculate the probability that it is actually raining.

• What is the probability of drawing three cards in increasing order from a shuffled deck of 500 cards? Imagine a deck of 500 cards numbered from 1 to 500. If you pick three cards one at a time, what is the probability that each subsequent card will be larger than the previous one?

• How would you test if survey responses were filled at random by certain individuals? You have survey data from multiple-choice questions. Describe how you would determine if some individuals filled out the survey randomly rather than truthfully.

• What is the probability of a biased coin landing heads exactly 5 times out of 6 tosses? Given a biased coin that lands heads 30% of the time, calculate the probability of getting heads exactly 5 times in 6 tosses.

• What kind of model did the co-worker develop for loan approval? Your co-worker developed a model that takes customer inputs and returns a decision on whether a loan should be given or not. What type of model is this?

• How would you compare two credit risk models for predicting loan defaults? Given that personal loans are monthly installments, how would you measure the difference between two credit risk models within a specific timeframe?

• What metrics would you track to measure the success of a new credit risk model? Identify the key metrics you would track to evaluate the performance of a new model predicting loan defaults.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. In which scenarios would you prefer a bagging algorithm over a boosting algorithm? Provide examples of the tradeoffs between the two.

• How would you detect firearm listings on a marketplace? Design a system to automatically detect if a listing on your website's marketplace is selling a gun, given that selling firearms is prohibited by your Terms of Service Agreement.

• How would you design a model to map legal first names to nicknames? As a data scientist at Facebook, you need to create a machine learning model that maps legal first names to likely nicknames. How would you approach designing this model?

• How would you tackle multicollinearity in multiple linear regression? Explain the methods you would use to address multicollinearity when performing multiple linear regression.

Interviewing for a Data Scientist position at Huron Consulting Group is an exciting journey where your analytical prowess and problem-solving skills can shine. If you want more insights about the company, check out our main Huron Consulting Group Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Huron Consulting Group’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Huron Consulting Group Data Scientist interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!