The University of Nebraska-Lincoln is a prestigious institution dedicated to fostering a diverse and inclusive work environment. As a leading university, it continually seeks to attract and retain a high-performing, diverse workforce. The Data Analyst position at the University of Nebraska-Lincoln provides an exciting opportunity to support media/marketing professionals or enhance the efficiency and scalability of Salesforce reporting structures, depending on the role.

In these roles, you will utilize data analytics and visualization tools to generate insights and guide business decisions, contributing to impactful storytelling, engaging audiences, and improving operational efficiency. If you are driven by curiosity and possess strong data skills, this guide will walk you through the interview process and offer tips to succeed in your application journey. Let's get started with Interview Query!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining the University of Nebraska-Lincoln as a Data Analyst. Whether you were contacted by a 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 Nebraska-Lincoln 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 hiring manager stays present during the screening round to answer your queries about the role and the university 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 Data Analyst 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 university’s data systems, ETL pipelines, and SQL queries.

In the case of data analyst 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 University of Nebraska-Lincoln 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 Analyst role at the University of Nebraska-Lincoln.

Quick Tips For University of Nebraska-Lincoln Data Analyst Interviews

• Research the University's Public Media Initiatives: Knowledge about Nebraska Public Media and its initiatives can help you understand the data's context you'll be working with.
• Technical Preparation: Brushing up on the software and statistical programming languages mentioned (e.g., Tableau, SPSS, R, Python, SAS) is crucial. Make sure you're comfortable with ETL processes as well.
• Cultural Fit: The University of Nebraska-Lincoln values diversity and inclusion. Be prepared to discuss how your values align with creating an inclusive work environment.

Typically, interviews at University Of Nebraska-Lincoln vary by role and team, but commonly Data Analyst 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? Mode sells B2B analytics dashboards and has various marketing channels with respective costs. Identify the key metrics to evaluate the value of each marketing channel.

• How would you measure the success of Facebook Groups? Determine the key metrics and criteria to evaluate the success and effectiveness of Facebook Groups.

• What key parameters would you focus on to improve customer experience on Uber Eats? Identify the main parameters that should be improved to enhance the customer experience on Uber Eats.

• How would you measure success for Facebook Stories? Specify the metrics and criteria you would use to evaluate the success of Facebook Stories.

• What do you think are the most important metrics for WhatsApp? Identify the most critical metrics to evaluate 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. Discuss the meaning of the coefficients in terms of odds ratios and how they impact the dependent variable.

• What are the assumptions of linear regression? List and explain the key assumptions underlying linear regression models. These include linearity, independence, homoscedasticity, normality, and no multicollinearity.

• How would you tackle multicollinearity in multiple linear regression? Describe methods to address multicollinearity in multiple linear regression. Discuss techniques such as variance inflation factor (VIF) analysis, removing highly correlated predictors, and using regularization methods like Ridge or Lasso regression.

• Let's say you have a categorical variable with thousands of distinct values, how would you encode it? Explain strategies for encoding a categorical variable with a large number of distinct values. Discuss methods like one-hot encoding, target encoding, and using embeddings.

• How would you handle the data preparation for building a machine learning model using imbalanced data? Describe the steps to prepare data for a machine learning model when dealing with imbalanced classes. Discuss techniques such as resampling (oversampling/undersampling), using different evaluation metrics, and applying algorithms designed to handle imbalanced data.

What is the average salary for a Data Analyst at University Of Nebraska-Lincoln?

Q: What is the role of a Media/Business Development Data Analyst at the University of Nebraska-Lincoln?

A: The Media/Business Development Data Analyst will assist in conducting research and analysis by standardizing and automating the collection, extraction, transformation, and storage of media/marketing data. The insights derived from this data guide business decisions for internal staff and reports for state and federal organizations.

Q: What qualifications are required for the Data Analyst positions?

A: For the Media/Business Development Data Analyst position, a minimum of an Associate's degree in media/marketing research, computer science, statistics, mathematics, or a related field, plus one year of professional or educational experience in market/media research, statistical analysis, and data management is required. The Salesforce Data Analyst position requires an Associate's in Computer Science, Business, Mathematics, Statistics, Social Science, or other quantitative fields, and three years of professional experience as a data analyst.

Q: How does the University of Nebraska-Lincoln support diversity and inclusion?

A: The University of Nebraska-Lincoln seeks to attract and retain a high-performing and diverse workforce. It fosters a diverse and inclusive work environment that respects and values employees' differences to better meet the varying needs of the diverse populations served. The university considers qualified applicants without regard to race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation.

Q: What tools and skills are preferred for these Data Analyst roles?

A: Preferred qualifications for the Media/Business Development Data Analyst include experience with data analytics software (e.g., Tableau, SPSS) and statistical programming languages (e.g., R, Python, SAS). For the Salesforce Data Analyst, experience with CRM or relational databases, data visualization tools (e.g., Tableau, Microsoft Power BI), and SQL query building is preferred.

Q: How can I apply for the Data Analyst positions at the University of Nebraska-Lincoln?

A: Interested candidates should click on "Apply for this Job" on the respective job posting. You will then either create an application or edit your current application on file. Attach your resume, cover letter, and a list of references as three separate documents in MS Word or PDF format. For more information, contact Nebraska Public Media Human Resources at humanresources@nebraskapublicmedia.org for the Media/Business Development Data Analyst position, or Sandy Airan at sairan2@unl.edu for the Salesforce Data Analyst position.

If you want more insights about the company, check out our main University Of Nebraska-Lincoln 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 the University Of Nebraska-Lincoln’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 University Of Nebraska-Lincoln data analyst 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!