First Horizon Bank Data Analyst Interview Questions + Guide in 2025

First Horizon Bank is a leading regional financial services company with over $85 billion in assets, dedicated to empowering clients, communities, and associates through capital and counsel.

As a Data Analyst at First Horizon Bank, your role will encompass a wide range of responsibilities centered around data analysis and reporting within the financial services industry. You will be tasked with extracting, manipulating, and interpreting complex datasets to support strategic decision-making processes. Key responsibilities include conducting in-depth analyses of financial data, generating reports and visualizations for senior leadership, and ensuring compliance with regulatory standards. A strong proficiency in SQL and familiarity with statistical concepts will be essential for success in this role.

The ideal candidate should possess a background in quantitative fields such as finance, mathematics, or statistics, coupled with excellent communication skills to convey findings effectively. Additionally, a collaborative mindset is crucial, as you will work with cross-functional teams to optimize data processes and enhance operational efficiency. Your ability to manage multiple priorities while maintaining attention to detail will set you apart as a vital team member.

This guide will provide you with insights and tailored preparation strategies to excel in your interview for the Data Analyst role at First Horizon Bank, ensuring you are equipped to demonstrate your analytical capabilities and alignment with the company's values.

The interview process for a Data Analyst position at First Horizon Bank is structured to assess both technical skills and cultural fit within the organization. Candidates can expect a series of interviews that evaluate their analytical capabilities, problem-solving skills, and familiarity with relevant tools and methodologies.

1. Initial Phone Screen

The first step in the interview process is typically a phone screen conducted by a member of the HR team. This initial conversation lasts about 30 minutes and focuses on understanding the candidate's background, experience, and motivation for applying to First Horizon Bank. The recruiter will also gauge the candidate's comfort level with SQL and other relevant analytical tools, as well as discuss the role's expectations and the company culture.

2. Technical Interview

Following the phone screen, candidates will participate in a technical interview, which is often conducted via video conferencing platforms like Webex. This interview is led by a hiring manager or a senior data analyst and delves deeper into the candidate's technical skills. Expect questions that assess proficiency in SQL, data analysis techniques, and familiarity with statistical concepts. Candidates may also be asked to solve practical problems or case studies that reflect real-world scenarios they might encounter in the role.

3. Behavioral Interview

The next stage is a behavioral interview, which aims to evaluate how candidates align with First Horizon Bank's values and culture. This interview typically involves discussing past experiences and how they relate to the competencies required for the Data Analyst role. Candidates should be prepared to share examples of teamwork, leadership, and how they have handled challenges in previous positions.

4. Final Interview

The final interview may involve a panel of interviewers, including team members from various departments. This round focuses on assessing the candidate's ability to collaborate across functions and their understanding of the banking industry. Candidates may be asked to present a data analysis project they have worked on, showcasing their analytical skills and ability to communicate complex information effectively to non-technical stakeholders.

5. Reference Check

After successfully completing the interviews, candidates may undergo a reference check. This step involves contacting previous employers or colleagues to verify the candidate's work history, skills, and overall fit for the role.

As you prepare for your interview, consider the specific skills and experiences that will be relevant to the questions you may encounter. Next, we will explore the types of interview questions that candidates have faced during the process.

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

Prepare for a Conversational Interview

The interview process at First Horizon Bank tends to be laid back, especially during the initial phone call with HR and subsequent discussions with team managers. Approach the interview as a conversation rather than a formal interrogation. This means being ready to engage in a dialogue about your experiences and how they relate to the role. Prepare thoughtful questions that demonstrate your interest in the team and the company, as this will help you build rapport with your interviewers.

Highlight Your Technical Proficiency

Given the emphasis on SQL and analytics in the role, ensure you can confidently discuss your experience with these tools. Be prepared to provide specific examples of how you've used SQL to solve problems or analyze data in previous roles. If you have experience with Python or other analytical tools, be ready to discuss how you've applied these skills in a practical context. Demonstrating your technical expertise will be crucial in showcasing your fit for the position.

Understand the Business Context

First Horizon Bank operates in a highly regulated financial environment, so it's important to understand the principles of Asset & Liability Management (ALM) and Funds Transfer Pricing (FTP). Familiarize yourself with how these concepts apply to the bank's operations and be prepared to discuss how your analytical skills can contribute to effective decision-making in these areas. This knowledge will not only help you answer questions more effectively but also show your commitment to understanding the business.

Communicate Clearly and Effectively

Strong communication skills are essential for a Data Analyst role, especially when conveying complex information to non-technical stakeholders. Practice explaining your analytical processes and findings in simple terms. Use examples from your past experiences to illustrate how you've successfully communicated insights to different audiences. This will demonstrate your ability to bridge the gap between technical analysis and business strategy.

Embrace a Growth Mindset

First Horizon values intellectual curiosity and a willingness to learn. During your interview, express your commitment to personal growth and openness to feedback. Share examples of how you've sought out new learning opportunities or adapted to challenges in your previous roles. This mindset aligns well with the company culture and will resonate positively with your interviewers.

Be Ready for Behavioral Questions

Expect behavioral questions that assess how you've handled challenges in the past. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Prepare specific examples that highlight your analytical skills, teamwork, and problem-solving abilities. This approach will help you provide clear and concise answers that demonstrate your qualifications for the role.

Show Enthusiasm for the Company Culture

First Horizon Bank prides itself on its commitment to equity and community engagement. Research the company's initiatives and values, and be prepared to discuss how they resonate with you. Showing genuine enthusiasm for the company's mission and culture can set you apart from other candidates and demonstrate your alignment with their values.

By following these tips, you'll be well-prepared to make a strong impression during your interview at First Horizon Bank. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at First Horizon Bank. The interview process will likely focus on your analytical skills, proficiency in SQL, and understanding of statistics and probability, as well as your ability to communicate complex data insights effectively. Be prepared to demonstrate your technical skills and provide examples from your past experiences.

SQL and Data Management

1. How comfortable are you with SQL, and can you describe a complex query you have written?

This question assesses your SQL proficiency and ability to handle complex data manipulations.

How to Answer

Discuss your experience with SQL, focusing on specific queries you've written that solved real business problems. Highlight your understanding of joins, subqueries, and aggregations.

Example

“I am very comfortable with SQL and have used it extensively in my previous roles. For instance, I wrote a complex query that joined multiple tables to analyze customer transaction patterns, which helped identify trends that informed our marketing strategy.”

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

This question tests your understanding of SQL joins and their implications on data retrieval.

How to Answer

Clearly define both types of joins and provide an example of when you would use each.

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 and matched rows from the right table, filling in NULLs where there are no matches. I typically use LEFT JOIN when I want to ensure I capture all records from the primary table, even if there are no corresponding records in the secondary table.”

3. Describe a time when you had to clean and prepare a dataset for analysis. What steps did you take?

This question evaluates your data preparation skills and attention to detail.

How to Answer

Outline the specific steps you took to clean the data, including handling missing values, removing duplicates, and ensuring data integrity.

Example

“In a previous project, I worked with a dataset that had numerous missing values and duplicates. I first identified and removed duplicates, then used imputation techniques to fill in missing values based on the mean of the relevant columns. Finally, I validated the dataset to ensure it was ready for analysis.”

4. How do you ensure the accuracy and integrity of your data analysis?

This question assesses your approach to data validation and quality assurance.

How to Answer

Discuss the methods you use to verify data accuracy, such as cross-referencing with other data sources or conducting sanity checks.

Example

“I ensure data accuracy by cross-referencing my findings with original data sources and conducting sanity checks. I also implement automated scripts to flag any anomalies in the data, which allows me to address potential issues before they affect my analysis.”

5. Can you describe your experience with data visualization tools? Which do you prefer and why?

This question gauges your familiarity with data visualization and your ability to communicate insights effectively.

How to Answer

Mention the tools you have used, your preferred tool, and why it stands out to you.

Example

“I have experience with Tableau and Power BI, but I prefer Tableau for its user-friendly interface and powerful visualization capabilities. I find it particularly effective for creating interactive dashboards that allow stakeholders to explore data insights on their own.”

Statistics and Probability

1. Explain the concept of p-value in hypothesis testing.

This question tests your understanding of statistical significance.

How to Answer

Define p-value and explain its role in hypothesis testing, including what it indicates about the null hypothesis.

Example

“The p-value measures the probability of obtaining results at least as extreme as the observed results, assuming the null hypothesis is true. A low p-value (typically < 0.05) indicates strong evidence against the null hypothesis, leading us to reject it.”

2. How would you approach a problem where you need to determine the correlation between two variables?

This question assesses your analytical thinking and understanding of correlation.

How to Answer

Outline the steps you would take to analyze the correlation, including data collection, analysis methods, and interpretation of results.

Example

“I would start by collecting data on the two variables and then use statistical software to calculate the correlation coefficient. After obtaining the coefficient, I would interpret the results to determine the strength and direction of the relationship, ensuring to visualize the data with a scatter plot for better understanding.”

3. Can you explain the difference between Type I and Type II errors?

This question evaluates your knowledge of statistical errors in hypothesis testing.

How to Answer

Define both types of errors and provide examples of each.

Example

“A Type I error occurs when we reject a true null hypothesis, while a Type II error happens when we fail to reject a false null hypothesis. For example, a Type I error could be concluding that a new drug is effective when it is not, while a Type II error would be failing to recognize that the drug is effective when it actually is.”

4. Describe a statistical method you have used to analyze data. What was the outcome?

This question allows you to showcase your practical experience with statistical methods.

How to Answer

Discuss a specific statistical method you applied, the context, and the results of your analysis.

Example

“I used regression analysis to predict customer churn based on various factors such as transaction frequency and customer service interactions. The model revealed that customers with fewer transactions were more likely to churn, which led to targeted retention strategies that reduced churn by 15%.”

5. How do you handle outliers in your data analysis?

This question assesses your approach to data integrity and analysis.

How to Answer

Explain your methods for identifying and addressing outliers, including any statistical techniques you use.

Example

“I identify outliers using box plots and z-scores. Depending on the context, I may choose to remove them if they are errors or analyze them separately if they provide valuable insights. For instance, in a sales dataset, an outlier might indicate a significant one-time purchase that could skew the overall analysis.”