Lehigh University Data Analyst Interview Questions + Guide in 2025

Lehigh University is a prestigious institution known for its commitment to academic excellence and a vibrant campus community.

As a Data Analyst at Lehigh University, you will be fundamental in driving data-informed strategic decisions that shape the university's direction. This role encompasses a variety of responsibilities, including managing special analytics projects, developing and maintaining data sources and pipelines, and creating insightful dashboards tailored to the needs of various stakeholders. Your strong proficiency in SQL and statistical analysis will be critical as you collaborate closely with the Director of Strategic Analytics to ensure data integrity and compliance while providing actionable insights.

To excel in this position, a Master's degree in a relevant field and several years of experience in data analysis—preferably within higher education—are essential. Familiarity with data visualization tools, particularly Tableau, and proficiency in programming languages such as R or Python will set you apart. The ideal candidate will not only possess exceptional analytical and problem-solving skills but also demonstrate a deep commitment to fostering an inclusive and equitable community, aligning with Lehigh University's core values.

This guide will equip you with the necessary insights and knowledge to stand out in your interview for the Data Analyst role at Lehigh University. By understanding the expectations and key competencies required, you will be better prepared to articulate your qualifications and demonstrate your fit for the position.

The interview process for a Data Analyst role at Lehigh University is structured to assess both technical skills and cultural fit within the institution. Here’s what you can expect:

1. Initial Screening

The first step in the interview process is typically a phone screening with a recruiter. This conversation lasts about 30 minutes and focuses on your background, experience, and motivation for applying to Lehigh University. The recruiter will also provide insights into the university's culture and values, ensuring that you align with their commitment to diversity and inclusion.

2. Technical Assessment

Following the initial screening, candidates usually undergo a technical assessment. This may be conducted via video call and involves a data-related task or case study. You will be evaluated on your proficiency in statistics, SQL, and data analysis tools such as R or Python. Expect to demonstrate your analytical thinking and problem-solving skills through practical scenarios that reflect the responsibilities of the role.

3. Behavioral Interviews

Candidates who successfully pass the technical assessment will be invited to participate in one or more behavioral interviews. These interviews are typically conducted by hiring managers and team members. They will focus on your past experiences, how you handle challenges, and your ability to collaborate with others. Be prepared to discuss specific examples that showcase your analytical skills, attention to detail, and communication abilities.

4. Final Interview

The final stage of the interview process may involve a more in-depth discussion with senior leadership or key stakeholders. This interview aims to assess your fit within the broader strategic goals of the university and your potential contributions to institutional decision-making. You may be asked to present a previous project or analysis you have conducted, highlighting your approach and the impact of your work.

As you prepare for your interview, consider the specific skills and experiences that will resonate with the interviewers, particularly in the areas of statistics, SQL, and data visualization. Next, let’s delve into the types of questions you might encounter during this process.

Here are some tips to help you excel in your interview.

Understand the Institutional Context

Lehigh University is deeply committed to fostering an inclusive and equitable community. Familiarize yourself with the university's mission, values, and recent initiatives, particularly those related to antiracism and diversity. This understanding will not only help you align your responses with the university's goals but also demonstrate your commitment to contributing positively to its culture.

Highlight Your Technical Proficiency

As a Data Analyst, you will be expected to have a strong command of SQL, statistical analysis, and data visualization tools like Tableau. Be prepared to discuss your experience with these tools in detail, including specific projects where you utilized them to drive insights or improve processes. Consider preparing a portfolio of your work or examples of dashboards you've created to showcase your skills effectively.

Emphasize Collaboration and Communication Skills

The role requires close collaboration with various stakeholders. Be ready to share examples of how you've successfully worked in teams, communicated complex data findings to non-technical audiences, and contributed to strategic decision-making. Highlight your ability to translate data into actionable insights that align with institutional goals.

Prepare for Behavioral Questions

Expect questions that assess your problem-solving abilities and how you handle challenges. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Think of specific instances where you overcame obstacles in data analysis or project management, and be sure to articulate the impact of your actions.

Showcase Your Passion for Higher Education

Lehigh University values candidates who are enthusiastic about contributing to the higher education landscape. Share your motivations for wanting to work in this sector and how your background aligns with the university's mission. Discuss any relevant experiences that demonstrate your commitment to educational excellence and data-driven decision-making.

Be Ready to Discuss Data Integrity and Compliance

Given the importance of data integrity in higher education, be prepared to discuss your experience ensuring data accuracy and compliance with relevant policies. Highlight any specific methodologies or tools you have used to maintain data quality and integrity in your previous roles.

Ask Insightful Questions

Prepare thoughtful questions that reflect your interest in the role and the university. Inquire about the specific challenges the Institutional Data department is currently facing, how success is measured in the role, and opportunities for professional development within the university. This will demonstrate your proactive approach and genuine interest in contributing to the team.

By following these tips, you will be well-prepared to showcase your skills and fit for the Data Analyst role at Lehigh University. Good luck!

Lehigh University Data Analyst Interview Questions

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Lehigh University. The interview will focus on your analytical skills, proficiency in statistical methods, and ability to manage and interpret data effectively. Be prepared to demonstrate your knowledge of SQL, statistical analysis, and data visualization tools, as well as your experience in higher education contexts.

Statistics and Probability

1. Can you explain the difference between descriptive and inferential statistics?

Understanding the distinction between these two branches of statistics is fundamental for a data analyst.

How to Answer

Describe how descriptive statistics summarize data from a sample, while inferential statistics use that sample data to make predictions or inferences about a larger population.

Example

“Descriptive statistics provide a summary of the data, such as mean and standard deviation, which helps in understanding the dataset. In contrast, inferential statistics allow us to draw conclusions about a population based on sample data, using techniques like hypothesis testing and confidence intervals.”

2. How do you handle missing data in a dataset?

Handling missing data is crucial for maintaining the integrity of your analysis.

How to Answer

Discuss various methods such as imputation, deletion, or using algorithms that support missing values, and explain your rationale for choosing a particular method.

Example

“I typically assess the extent of missing data first. If it’s minimal, I might use mean imputation. For larger gaps, I prefer to use predictive modeling techniques to estimate missing values, ensuring that the integrity of the dataset is maintained.”

3. What statistical tests would you use to compare the means of two groups?

This question assesses your knowledge of hypothesis testing.

How to Answer

Mention tests like the t-test or ANOVA, and explain when you would use each.

Example

“I would use a t-test if I’m comparing the means of two independent groups. If I have more than two groups, I would opt for ANOVA to determine if there are any statistically significant differences among them.”

4. Explain the concept of p-value and its significance in hypothesis testing.

Understanding p-values is essential for interpreting statistical results.

How to Answer

Define p-value and discuss its role in determining the significance of results in hypothesis testing.

Example

“A p-value indicates the probability of observing the data, or something more extreme, if the null hypothesis is true. A low p-value (typically < 0.05) suggests that we can reject the null hypothesis, indicating that our findings are statistically significant.”

SQL and Data Management

1. How do you optimize a SQL query for better performance?

This question tests your practical SQL skills and understanding of database management.

How to Answer

Discuss techniques such as indexing, avoiding SELECT *, and using JOINs efficiently.

Example

“To optimize a SQL query, I would first ensure that the necessary indexes are in place for the columns used in WHERE clauses. I also avoid using SELECT * and instead specify only the columns I need, which reduces the amount of data processed.”

2. Can you explain the difference between INNER JOIN and LEFT JOIN?

Understanding joins is critical for data manipulation in SQL.

How to Answer

Clarify how INNER JOIN returns only matching rows, while LEFT JOIN returns all rows from the left table and matched rows from the right.

Example

“An INNER JOIN returns only the rows where there is a match in both tables, while a LEFT JOIN returns all rows from the left table, along with matched rows from the right table. If there’s no match, NULL values are returned for the right table’s columns.”

3. Describe a complex SQL query you have written and its purpose.

This question allows you to showcase your SQL expertise and problem-solving skills.

How to Answer

Provide a brief overview of the query, what it accomplished, and any challenges you faced.

Example

“I wrote a complex SQL query to analyze student enrollment trends over five years. It involved multiple JOINs across several tables and used window functions to calculate year-over-year growth rates. The challenge was ensuring data integrity across different sources, which I managed by implementing rigorous validation checks.”

4. How do you ensure data quality and integrity in your analyses?

Data quality is paramount in any analytical role.

How to Answer

Discuss methods such as validation checks, data cleaning processes, and regular audits.

Example

“I ensure data quality by implementing validation checks at the data entry stage and conducting regular audits of the datasets. I also use data cleaning techniques to handle inconsistencies and outliers, ensuring that my analyses are based on accurate and reliable data.”

Data Visualization and Reporting

1. What tools do you use for data visualization, and why?

This question assesses your familiarity with visualization tools.

How to Answer

Mention specific tools like Tableau or Power BI and discuss their strengths.

Example

“I primarily use Tableau for data visualization due to its user-friendly interface and powerful capabilities for creating interactive dashboards. It allows me to present complex data in a visually appealing way, making it easier for stakeholders to understand insights.”

2. How do you approach creating a dashboard for stakeholders?

This question evaluates your ability to communicate data effectively.

How to Answer

Discuss your process for understanding stakeholder needs, selecting relevant metrics, and designing the dashboard.

Example

“I start by meeting with stakeholders to understand their specific needs and the key metrics they want to track. I then design the dashboard to highlight these metrics clearly, ensuring it’s intuitive and easy to navigate, while also allowing for drill-down capabilities for deeper insights.”

3. Can you give an example of a time when your data visualization influenced a decision?

This question allows you to demonstrate the impact of your work.

How to Answer

Share a specific instance where your visualization led to actionable insights.

Example

“I created a dashboard that visualized student retention rates by demographic factors. This visualization highlighted significant trends that prompted the administration to implement targeted support programs, ultimately improving retention rates by 10% in the following year.”

4. How do you ensure that your reports are accessible to non-technical stakeholders?

This question assesses your ability to communicate complex data simply.

How to Answer

Discuss strategies for simplifying data presentations and using clear language.

Example

“I focus on using clear, non-technical language in my reports and visualizations. I also include summaries and key takeaways at the beginning of my reports, ensuring that non-technical stakeholders can grasp the main insights without getting lost in the details.”