Ut Health Houston is a leading academic health center renowned for its innovative advancements in healthcare and biomedical sciences. With a commitment to transforming health and improving lives, it stands at the forefront of medical research and education.

In the Business Intelligence position, you will be pivotal in driving data-driven decisions across various departments. This role involves extracting, analyzing, and interpreting complex datasets to help streamline processes and enhance performance. The interview process typically begins with a phone screen by a recruiter or HR personnel, followed by an in-person interview with the hiring manager. The final step involves delivering a short presentation to a panel.

Leverage this Interview Query guide to navigate the process with confidence. We’ll explore common questions, share insights, and offer valuable tips to help you succeed in your interview for this impactful role.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining UT Health Houston as a Business Intelligence professional. Whether you were contacted by a UT Health Houston 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 UT Health Houston 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 UT Health Houston Business Intelligence hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also engage 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 UT Health Houston Business Intelligence role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around ETL pipelines, SQL queries, and data visualization.

In the case of Business Intelligence roles, take-home assignments regarding product metrics, analytics, and data visualization are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and fundamental BI tools 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 UT Health Houston office. Your technical prowess, including programming and BI tool 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 Business Intelligence role at UT Health Houston.

Quick Tips For UT Health Houston Business Intelligence Interviews

• Express Clearly: Ensure that you can articulate your thoughts in a clear and coherent manner. This will be very helpful in interviews for Business Intelligence roles where communication of complex ideas is key.
• Prepare for Behavioral Questions: Be ready to answer questions like "Why should we hire you?” and “Describe a difficult situation you have encountered with a co-worker on a project and how did you help improve the situation.”
• Know Technical Fundamentals: Brush up on fundamental technical questions such as “How would you reverse a linked list?” and other core concepts related to data analysis and business intelligence.

Typically, interviews at Ut Health Houston vary by role and team, but commonly Business Intelligence interviews follow a fairly standardized process across these question topics.

• What are the Z and t-tests, and when should you use each? Explain the purpose and differences between Z and t-tests. Describe scenarios where one test is preferred over the other.

• How would you reformat student test score data for better analysis? Given two datasets of student test scores, identify drawbacks in their current format. Suggest formatting changes and discuss common issues in "messy" datasets.

• What metrics would you use to evaluate the value of marketing channels? Given data on marketing channels and costs for a B2B analytics dashboard company, identify key metrics to determine the value of each marketing channel.

• How would you determine the next partner card using customer spending data? With access to customer spending data, outline the process to identify the best partner for a new credit card offering.

• How would you investigate if a redesigned email campaign led to increased conversion rates? Analyze the impact of a redesigned email campaign on conversion rates, considering other potential factors that could influence the observed increase.

• Write a function search_list to check if a target value is in a linked list. Write a function, search_list, that returns a boolean indicating if the target value is in the linked_list or not. You receive the head of the linked list, which is a dictionary with value and next keys. If the linked list is empty, you'll receive None.

• Write a query to find users who placed less than 3 orders or ordered less than $500 worth of product. Write a query to identify the names of users who placed less than 3 orders or ordered less than $500 worth of product. Use the transactions, users, and products tables.

• Create a function digit_accumulator to sum every digit in a string representing a floating-point number. You are given a string that represents some floating-point number. Write a function, digit_accumulator, that returns the sum of every digit in the string.

• Develop a function to parse the most frequent words used in poems. You're hired by a literary newspaper to parse the most frequent words used in poems. Poems are given as a list of strings called sentences. Return a dictionary of the frequency that words are used in the poem, processed as lowercase.

• Write a function rectangle_overlap to determine if two rectangles overlap. You are given two rectangles a and b each defined by four ordered pairs denoting their corners on the x, y plane. Write a function rectangle_overlap to determine whether or not they overlap. Return True if so, and False otherwise.

• How would you design a function to detect anomalies in univariate and bivariate datasets? If given a univariate dataset, how would you design a function to detect anomalies? What if the data is bivariate?

• What are the drawbacks of the given student test score data layouts? Assume you have data on student test scores in two layouts. What are the drawbacks of these layouts? What formatting changes would you make for better analysis? Describe common problems in “messy” datasets.

• What is the expected churn rate in March for customers who bought subscriptions since January 1st? You noticed that 10% of customers who bought subscriptions in January 2020 canceled before February 1st. Assuming uniform new customer acquisition and a 20% month-over-month decrease in churn, what is the expected churn rate in March for all customers since January 1st?

• How would you explain a p-value to a non-technical person? How would you explain what a p-value is to someone who is not technical?

• What are Z and t-tests, and when should you use each? What are the Z and t-tests? What are they used for? What is the difference between them? When should you use one over the other?

• How does random forest generate the forest and why use it over logistic regression? Explain how random forest generates multiple decision trees and why it might be preferred over logistic regression in certain scenarios.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms and provide examples of tradeoffs between using bagging and boosting algorithms.

• How would you evaluate and compare two credit risk models for personal loans?

• Identify the type of model developed to decide loan approval.
• Describe how to measure the difference between two models predicting loan defaults over time.

• List metrics to track the success of the new model.

• What’s the difference between Lasso and Ridge Regression? Explain the key differences between Lasso and Ridge Regression techniques.

• What are the key differences between classification models and regression models? Describe the main differences between classification and regression models in machine learning.

What is the average salary for a Business Intelligence at Ut Health Houston?

Q: What is the interview process for the Business Intelligence position at UT Health Houston like?
The interview process at UT Health Houston starts with a phone screen by a recruiter or HR personnel. The second step involves an in-person interview with the hiring manager. Finally, candidates are asked to give a short presentation to a panel.

Q: What types of technical questions can I expect in the interview?
You may be asked a variety of technical questions, such as "How would you reverse a linked list?" to assess your problem-solving skills and technical expertise. Be prepared to discuss your thought process and approach.

Q: How can I prepare for behavioral questions in the interview?
You should be ready to discuss past experiences, such as dealing with difficult situations with co-workers. Questions like "Describe a difficult situation you have encountered with a co-worker on a project and how did you help improve the situation?" are common. Practice articulating your thoughts clearly and focusing on how you contributed positively to the outcome.

Q: How should I structure my presentation for the panel?
The presentation should be concise, clear, and focused on your expertise and experiences relevant to the Business Intelligence role. Make sure to highlight your unique contributions and problem-solving skills to make a strong impression.

Q: Why should I consider working at UT Health Houston?
UT Health Houston offers an engaging and supportive work environment where your contributions in the field of Business Intelligence can significantly impact healthcare outcomes. The emphasis on innovation and problem-solving makes it a dynamic place to grow your career.

If you want more insights about the company, check out our main UT Health Houston 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 UT Health Houston’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 UT Health Houston Business Intelligence 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!