Insurify Data Analyst Interview Questions + Guide in 2024

Insurify is a forward-thinking company in the insurance comparison industry, utilizing the latest in data technology to disrupt and innovate the market. The company is dedicated to providing consumers with the best possible experience when comparing insurance rates and policies, making it a vibrant place to grow your career as a data analyst.

The Data Analyst role at Insurify encompasses various responsibilities, from take-home assignments and SQL/Python challenges to in-depth statistical analysis and data modeling tasks. The interview process involves multiple stages, including an initial HR interview, a technical take-home assessment, an interview with the hiring manager, and team interviews that test your analytical prowess and cultural fit.

To navigate this competitive process successfully, our guide will provide you with insights and tips for each stage of the interview, commonly asked Insurify data analyst interview questions, and practical advice tailored to the company’s unique interviewing standards. Let’s get started!

The interview process usually depends on the role and seniority; however, you can expect the following on an Insurify data analyst interview:

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Insurify 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. Make sure you also have the opportunity to ask your own questions during this phase.

In some cases, the Insurify data analyst 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.

Take-Home Assessment

Successfully navigating the recruiter round will present you with an invitation to complete a take-home assessment. This assessment often takes about half to a full day of work and generally includes tasks focusing on SQL, Python, statistics, and possibly some simple coding challenges, such as a variant of Fizz Buzz.

The assessment is designed to evaluate your analytical skills, problem-solving capabilities, and your proficiency in data visualization.

This take-home test is quite comprehensive and may take anywhere from 5 to 10 hours to complete thoroughly. It involves building several models and could be time-consuming.

Interview with Hiring Manager

After passing the take-home assessment, you will have a meeting with the Insurify hiring manager. This interview is geared towards discussing the results and process of your take-home assessment. You may also expect some additional questions regarding statistics, SQL, or Python.

Keep an eye out for logistical issues—a delayed interviewer or lack of communication could inadvertently affect your experience. Some candidates have found this round to include random probability questions which might not directly relate to the job but aim to understand your critical thinking.

Onsite Interview Rounds

Following a successful interview with the hiring manager, you will be invited to attend the onsite interview loop. This involves multiple interview rounds with different members of the Insurify team. Prepare for SQL joins, average calculation questions, brainteasers, and situational problem-solving tasks.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview. This stage tests your overall technical rigor, communication skills, and how well you mesh with the team.

Typically, interviews at Insurify vary by role and team, but common data analyst interviews follow a fairly standardized process across these question topics.

1. What are the upper and lower bounds for the proportion of the population that likes both tea and coffee?

A survey asked 100 respondents if they liked tea and coffee. 70% liked coffee, 80% liked tea, and 10% liked neither. Based on this survey, determine the upper and lower bounds for the proportion of the population that likes both tea and coffee.

2. Write a SQL query to select the 2nd highest salary in the engineering department.

Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

3. Write a function get_ngrams to return a dictionary of n-grams and their frequency in a string.

Write a function get_ngrams to take in a word (string) and return a dictionary of n-grams and their frequency in the given string.

4. Write a function to determine if a string is a palindrome.

Given a string, write a function to determine if it is a palindrome. A palindrome reads the same forwards and backward.

5. Write a query to find users currently “Excited” and never “Bored” with a campaign.

Write a query to find all users that are currently “Excited” and have never been “Bored” with a campaign.

6. Write a function moving_window to find the moving window average of a list of numbers.

Given a list of numbers nums and an integer window_size, write a function moving_window to find the moving window average.

7. How would you determine if the redesigned email campaign led to the increase in conversion rate?

A new marketing manager redesigned the new-user email journey, and the conversion rate increased from 40% to 43%. However, the conversion rate was 45% a few months prior before dropping to 40%. Investigate whether the redesigned email campaign caused the increase or if other factors were responsible.

8. What methods could you use to increase recall in product search results without changing the search algorithm?

As a data scientist at Amazon, you want to improve the search results for product searches but cannot change the underlying logic in the search algorithm. What methods could you use to increase recall?

9. What metrics would you use to track the accuracy and validity of a spam classifier model?

You are tasked with building a spam classifier for emails and have built a V1 of the model. What metrics would you use to track the accuracy and validity of the model?

10. How would you justify the complexity of a neural network model and explain its predictions to non-technical stakeholders?

Your manager asks you to build a model with a neural network to solve a business problem. How would you justify the complexity of building such a model and explain the predictions to non-technical stakeholders?

11. How would you evaluate and validate a decision tree model for predicting loan repayment?

As a data scientist at a bank, you are tasked with building a decision tree model to predict if a borrower will pay back a personal loan. How would you evaluate whether using a decision tree algorithm is the correct model for the problem? How would you evaluate the performance of the model before and after deployment?

12. When would you use a bagging algorithm versus a boosting algorithm?

You are comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? Provide an example of the tradeoffs between the two.

Here are some tips to help you succeed on your Insurify data analyst interview:

1. Be Detail-Oriented: Insurify’s interviews may include specific technical questions, so it’s crucial to brush up on SQL, Python, and statistical methods. Practice these skills on Interview Query to be fully prepared.

2. Time Management: The take-home assessments can be time-consuming. Allocate your time efficiently to complete this phase well.

3. Stay Positive and Inquisitive: Demonstrating curiosity and a positive attitude, even if faced with unexpected or offbeat questions, can make a great impression.

What is the average salary for a Data Analyst at Insurify?

According to Glassdoor, data analysts at Insurify earn between $74K to $103K per year, with an average of $88K per year.

Are there any specific technical skills required for this position?

Yes, a strong grasp of SQL and Python is essential. You should also be proficient in statistics and data modeling. Experience with data visualization tools and statistical software will be beneficial.

How should I prepare for the interview process at Insurify?

To prepare effectively, research the company and understand its services. Practice common interview questions and technical tests on platforms like Interview Query. Be ready to discuss your past experiences, projects, and how they align with the role you are applying for.

If you’re considering a Data Analyst position at Insurify, it’s crucial to be prepared for a rigorous and somewhat unpredictable interview process.

For a more strategic approach to your preparation, we recommend utilizing Interview Query’s Insurify Interview Guide. This resource will arm you with the necessary insights and common questions, helping you navigate the interview landscape at Insurify effectively.

Good luck with your interview, and may your next opportunity be the perfect fit!