Huntington National Bank Product Analyst Interview Questions + Guide in 2025

Huntington National Bank is committed to delivering exceptional banking services while prioritizing a culture of teamwork and collaboration among its employees.

As a Product Analyst at Huntington National Bank, you will play a pivotal role within the Model Management and Optimization (MMO) team, focusing on the development and maintenance of products and models that ensure compliance with BSA/AML and OFAC regulations. Your key responsibilities will include engaging with stakeholders to define business objectives, documenting user stories, and refining product features to enhance operational efficiency. You will be expected to champion transformational change within BSA Operations, utilizing agile or hybrid methodologies to expedite project value.

To excel in this role, you should possess a solid background in risk management or business analysis, particularly in relation to compliance programs. Strong communication skills are essential, as you will be interacting with users of varying technical expertise and senior management. Additionally, familiarity with tools such as SQL, data analysis platforms, and project management software will be crucial for success. Traits such as attention to detail, problem-solving abilities, and a commitment to continuous improvement will make you an outstanding fit for Huntington's collaborative environment.

This guide will help you prepare for your interview by providing insights into the expectations and skills needed for the Product Analyst role, allowing you to present yourself confidently and effectively.

The interview process for a Product Analyst at Huntington National Bank is structured to assess both technical skills and cultural fit within the organization. It typically consists of several rounds, each designed to evaluate different aspects of your qualifications and experiences.

1. Initial Phone Interview

The process begins with a phone interview, usually conducted by a member of the Human Resources team. This initial conversation lasts about 30 minutes and focuses on your background, experiences, and motivations for applying to Huntington. Expect to discuss your resume in detail, as the interviewer will want to understand your previous projects and how they relate to the role of a Product Analyst. This is also an opportunity for you to learn about the company culture and the expectations for the position.

2. Technical and Behavioral Interviews

Following the initial screen, candidates typically participate in two rounds of in-person interviews. The first interview is often with the hiring manager, where you will delve deeper into your technical skills and relevant experiences. This round may include case studies or situational questions that require you to demonstrate your analytical thinking and problem-solving abilities. The second interview usually involves a senior leader or department head, focusing on your fit within the team and your understanding of the BSA/AML compliance landscape. Be prepared to discuss your familiarity with relevant tools and methodologies, as well as your approach to teamwork and collaboration.

3. Cultural Fit Assessment

Throughout the interview process, there is a strong emphasis on cultural fit. Interviewers will assess your alignment with Huntington's values and your ability to work effectively in a team-oriented environment. Expect questions that explore your long-term career goals and how you envision contributing to the department's strategic initiatives. The interviewers will be interested in your ability to communicate complex concepts clearly and your experience in managing multiple projects simultaneously.

4. Final Steps

After the interviews, candidates may receive a tour of the office and an introduction to potential team members, which helps to gauge the work environment and team dynamics. The entire process is designed to be thorough yet efficient, with a focus on ensuring that candidates not only possess the necessary skills but also align with the company's mission and values.

As you prepare for your interviews, consider the specific skills and experiences that will be relevant to the questions you may encounter.

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

Emphasize Your Relevant Experience

Given that interviewers at Huntington National Bank focus heavily on your background and previous projects, be prepared to discuss your resume in detail. Highlight specific experiences that relate to product analysis, risk management, and compliance programs. Be ready to explain the methodologies you used, the challenges you faced, and the outcomes of your projects. This will demonstrate your hands-on experience and your ability to contribute to the team.

Showcase Your Teamwork Skills

Huntington values collaboration and teamwork, so be sure to illustrate your ability to work effectively within a team. Share examples of how you have successfully collaborated with cross-functional teams in the past, particularly in fast-paced environments. Discuss how you’ve contributed to team goals and how you handle differing opinions or conflicts within a group setting. This will show that you align with the company culture and can thrive in their work environment.

Prepare for Technical Questions

While the interviews may be somewhat casual, you should still be ready for technical questions related to product metrics, SQL, and analytics. Brush up on your knowledge of these areas, as they are crucial for the role. Be prepared to discuss how you would apply these skills in real-world scenarios, particularly in relation to BSA/AML compliance and operational forecasting. This will demonstrate your technical proficiency and your understanding of the role's requirements.

Understand the Company Culture

Huntington places a strong emphasis on its culture, which values professionalism and a supportive environment. During your interviews, engage with your interviewers about their experiences at the company and what they enjoy about working there. This not only shows your interest in the company but also helps you gauge if it’s the right fit for you. Be genuine in your responses and express your enthusiasm for potentially joining their team.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your problem-solving abilities and how you handle challenges. Use the STAR (Situation, Task, Action, Result) method to structure your responses. This will help you provide clear and concise answers that highlight your skills and experiences. Additionally, be prepared to discuss your long-term career goals and how they align with Huntington’s objectives, as this will show your commitment to growth within the organization.

Follow Up with Insightful Questions

At the end of your interviews, take the opportunity to ask insightful questions about the team dynamics, ongoing projects, and the future direction of the department. This not only demonstrates your interest in the role but also allows you to assess if the position aligns with your career aspirations. Tailor your questions based on the information shared during the interview to show that you were actively listening and engaged.

By following these tips, you will be well-prepared to make a strong impression during your interview for the Product Analyst role at Huntington National Bank. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Product Analyst interview at Huntington National Bank. The interview process will likely focus on your experience with product metrics, SQL, and your understanding of machine learning concepts, as well as your ability to communicate effectively with stakeholders.

Product Metrics

1. How do you define and measure product success?

Understanding product metrics is crucial for a Product Analyst role. Be prepared to discuss specific metrics you have used in the past.

How to Answer

Discuss the key performance indicators (KPIs) you consider essential for measuring product success, and provide examples of how you have tracked and reported these metrics.

Example

“I define product success through a combination of user engagement metrics, conversion rates, and customer satisfaction scores. For instance, in my previous role, I implemented a dashboard that tracked these KPIs, which helped us identify areas for improvement and ultimately increased our user retention by 20%.”

2. Can you describe a time when you used data to influence a product decision?

This question assesses your analytical skills and your ability to leverage data for decision-making.

How to Answer

Share a specific example where your analysis led to a significant product change or improvement, emphasizing the data you used and the outcome.

Example

“In a previous project, I analyzed user feedback and usage data, which revealed that a significant portion of users were dropping off at a specific point in the onboarding process. By presenting this data to the product team, we were able to redesign the onboarding flow, resulting in a 30% increase in completion rates.”

3. What methods do you use to prioritize product features?

Prioritization is key in product management, and interviewers want to know your approach.

How to Answer

Discuss frameworks or methodologies you use for prioritization, such as the MoSCoW method or RICE scoring, and provide an example of how you applied it.

Example

“I typically use the RICE scoring model to prioritize features based on Reach, Impact, Confidence, and Effort. For example, in a recent project, I scored potential features and presented the findings to stakeholders, which helped us focus on high-impact features that aligned with our strategic goals.”

4. How do you ensure that your product metrics align with business objectives?

This question evaluates your understanding of aligning product goals with broader business strategies.

How to Answer

Explain how you connect product metrics to business objectives and provide an example of how you have done this in the past.

Example

“I ensure alignment by regularly collaborating with stakeholders to understand their objectives and translating those into measurable product metrics. For instance, when our company aimed to increase market share, I developed metrics that tracked user acquisition and retention, which directly supported our growth strategy.”

SQL

1. Can you explain the difference between INNER JOIN and LEFT JOIN in SQL?

SQL skills are essential for a Product Analyst, and understanding joins is fundamental.

How to Answer

Clearly explain the differences between the two types of joins and provide a scenario where each would be used.

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, with NULLs for non-matching rows. For example, if I wanted to list all customers and their orders, I would use a LEFT JOIN to ensure I include customers who haven’t placed any orders.”

2. How would you write a SQL query to find the top 10 customers by total spend?

This question tests your practical SQL skills.

How to Answer

Outline the steps you would take to write the query, including any necessary aggregations and sorting.

Example

“I would use a SELECT statement with SUM to aggregate the total spend per customer, followed by a GROUP BY clause to group the results by customer ID. Finally, I would use ORDER BY to sort the results in descending order and LIMIT to return the top 10 customers.”

3. Describe a complex SQL query you have written. What was its purpose?

This question assesses your experience with more advanced SQL queries.

How to Answer

Provide a specific example of a complex query, explaining its purpose and the logic behind it.

Example

“I once wrote a complex SQL query to analyze customer behavior over time. The query involved multiple JOINs across several tables to pull in transaction data, customer demographics, and product information. The goal was to identify trends in purchasing patterns, which helped inform our marketing strategy.”

4. How do you optimize SQL queries for performance?

Performance optimization is crucial for handling large datasets.

How to Answer

Discuss techniques you use to improve query performance, such as indexing or query restructuring.

Example

“I optimize SQL queries by analyzing execution plans to identify bottlenecks, using indexes to speed up searches, and restructuring queries to reduce complexity. For instance, I once improved a slow-running report by adding indexes on frequently queried columns, which reduced the execution time by over 50%.”

Machine Learning

1. What is your experience with machine learning models?

This question gauges your familiarity with machine learning concepts.

How to Answer

Discuss any relevant experience you have with machine learning, including specific models or projects.

Example

“I have experience working with regression models and decision trees in Python. In a recent project, I developed a predictive model to forecast customer churn, which involved data preprocessing, feature selection, and model evaluation, ultimately leading to actionable insights for the marketing team.”

2. How do you evaluate the performance of a machine learning model?

Understanding model evaluation is key for a Product Analyst.

How to Answer

Explain the metrics you use to evaluate model performance and why they are important.

Example

“I evaluate machine learning models using metrics such as accuracy, precision, recall, and F1 score, depending on the problem type. For instance, in a classification task, I focus on precision and recall to ensure that the model is not only accurate but also minimizes false positives and negatives.”

3. Can you explain the concept of overfitting in machine learning?

This question tests your understanding of common machine learning pitfalls.

How to Answer

Define overfitting and discuss how to prevent it.

Example

“Overfitting occurs when a model learns the training data too well, capturing noise instead of the underlying pattern, which leads to poor performance on unseen data. To prevent overfitting, I use techniques such as cross-validation, regularization, and pruning in decision trees.”

4. Describe a project where you applied machine learning to solve a business problem.

This question assesses your practical application of machine learning.

How to Answer

Share a specific project, detailing the problem, the approach you took, and the outcome.

Example

“I worked on a project to predict loan defaults using logistic regression. By analyzing historical loan data and customer profiles, I built a model that identified high-risk applicants. This model helped the risk management team reduce defaults by 15% in the following quarter.”