Old National Bank has been a vital partner in its communities since 1834, focused on helping clients achieve their financial goals while maintaining a strong commitment to social responsibility.

The Data Analyst at Old National Bank plays a crucial role in leveraging data to support decision-making processes across various departments. This position involves collecting, analyzing, and interpreting complex data sets to provide insights that drive strategic initiatives. Key responsibilities include performing statistical analyses, developing and maintaining dashboards, and utilizing SQL to manage and query large databases. A successful Data Analyst will exhibit strong analytical and problem-solving skills, as well as a deep understanding of statistics and probability. Experience with algorithms and analytical tools will be highly beneficial. Additionally, the ability to communicate findings effectively to stakeholders is essential, aligning with the bank's values of collaboration and inclusion.

This guide will equip you with the knowledge and confidence needed to excel in your interview for a Data Analyst position at Old National Bank, ensuring you can showcase your skills and align with the company's mission.

The interview process for a Data Analyst role at Old National Bank is structured to assess both technical skills and cultural fit within the organization. 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 Old National Bank. The recruiter will also provide insights into the company culture and the specifics of the Data Analyst role, ensuring that you understand the expectations and responsibilities.

2. Technical Assessment

Following the initial screening, candidates usually undergo a technical assessment. This may be conducted via a video call with a current Data Analyst or a member of the analytics team. During this session, you will be evaluated on your proficiency in statistics, probability, and SQL. Expect to solve practical problems that demonstrate your analytical skills and ability to interpret data effectively. You may also be asked to discuss past projects or experiences that highlight your technical capabilities.

3. Behavioral Interview

After successfully completing the technical assessment, candidates typically participate in a behavioral interview. This round often involves multiple interviewers, including team members and managers. The focus here is on your soft skills, such as communication, problem-solving, and collaboration. You will be asked to provide examples of how you have handled challenges in previous roles, worked in teams, and contributed to projects. This is an opportunity to showcase your alignment with Old National Bank's core values of optimism, collaboration, and inclusivity.

4. Final Interview

The final stage of the interview process usually involves a more in-depth discussion with senior management or executives. This interview may cover strategic thinking, your understanding of the banking industry, and how you can contribute to the organization’s goals. You may also be asked about your long-term career aspirations and how they align with the bank's mission and values.

5. Reference Check

If you successfully navigate the interview rounds, the final step is a reference check. The recruiter will reach out to your previous employers or colleagues to verify your work history and assess your fit for the role and company culture.

As you prepare for your interviews, consider the specific questions that may arise in each of these stages.

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

Understand the Company’s Values and Culture

Old National Bank prides itself on its commitment to social responsibility, community engagement, and diversity. Familiarize yourself with their core values: optimism, collaboration, inclusivity, agility, and ethics. Be prepared to discuss how your personal values align with these principles and how you can contribute to fostering an inclusive workplace.

Highlight Your Analytical Skills

As a Data Analyst, your proficiency in statistics and probability will be crucial. Brush up on key statistical concepts and be ready to discuss how you have applied these skills in previous roles. Prepare examples that demonstrate your ability to analyze data, draw insights, and make data-driven decisions.

Master SQL and Data Tools

SQL is a vital skill for this role. Ensure you are comfortable with writing complex queries, including joins, subqueries, and aggregations. If you have experience with data visualization tools or programming languages like Python or R, be ready to discuss how you have used them to enhance your data analysis capabilities.

Prepare for Problem-Solving Scenarios

Expect to encounter questions that assess your problem-solving abilities. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Think of specific instances where you identified a problem, analyzed data to understand it, and implemented a solution that had a positive impact.

Communicate Effectively

Strong communication skills are essential for a Data Analyst, especially when presenting findings to stakeholders. Practice articulating complex data insights in a clear and concise manner. Be prepared to explain your thought process and the rationale behind your analyses, ensuring that you can tailor your communication style to different audiences.

Show Your Commitment to Continuous Learning

Old National Bank values team members who are eager to grow and develop. Share examples of how you have pursued professional development, whether through formal education, certifications, or self-directed learning. Highlight your adaptability and willingness to stay current with industry trends and technologies.

Build Relationships and Collaborate

Collaboration is key in this role. Be ready to discuss how you have worked effectively within cross-functional teams in the past. Emphasize your ability to build relationships with colleagues and stakeholders, and how you can leverage these relationships to drive successful outcomes.

Be Authentic and Engaged

Finally, be yourself during the interview. Old National Bank seeks individuals who are not only skilled but also genuinely passionate about their work and the communities they serve. Show enthusiasm for the role and the company, and be prepared to discuss why you are excited about the opportunity to contribute to Old National Bank’s mission.

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

Old National Bank Data Analyst Interview Questions

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Old National Bank. The interview will likely focus on your analytical skills, understanding of statistics and probability, and your ability to work with SQL and data analytics tools. Be prepared to demonstrate your problem-solving abilities and your understanding of data-driven decision-making in a financial context.

Statistics and Probability

1. Can you explain the difference between Type I and Type II errors in hypothesis testing?

Understanding the implications of these errors is crucial in data analysis, especially in a financial institution where decisions can have significant consequences.

How to Answer

Discuss the definitions of both errors and provide examples of how they might impact decision-making in a banking context.

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 instance, in a credit risk model, a Type I error could mean denying a loan to a creditworthy applicant, while a Type II error might involve approving a loan for someone who is likely to default.”

2. How would you approach a situation where your data analysis contradicts the business's expectations?

This question assesses your ability to communicate and defend your findings.

How to Answer

Emphasize the importance of data integrity and the need for open communication with stakeholders.

Example

“I would first ensure that my analysis is accurate and double-check the data sources. Then, I would present my findings to the relevant stakeholders, explaining the methodology and the implications of the results. It’s essential to foster a dialogue to understand their expectations and provide insights based on the data.”

3. Describe a statistical method you have used in your previous work and its impact.

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

How to Answer

Choose a method relevant to the banking sector, such as regression analysis or time series forecasting, and explain its application.

Example

“I utilized logistic regression to predict customer churn rates. By analyzing various customer attributes, we identified key factors leading to churn, which allowed us to implement targeted retention strategies, ultimately reducing churn by 15% over six months.”

4. What is the Central Limit Theorem, and why is it important in data analysis?

This question tests your foundational knowledge of statistics.

How to Answer

Explain the theorem and its significance in making inferences about populations based on sample data.

Example

“The Central Limit Theorem states that the distribution of sample means approaches a normal distribution as the sample size increases, regardless of the population's distribution. This is crucial in data analysis because it allows us to make reliable inferences about a population from sample data, which is often the case in financial analysis.”

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

Handling missing data is a common challenge in data analysis.

How to Answer

Discuss various techniques for dealing with missing data, such as imputation or exclusion, and the rationale behind your choice.

Example

“I typically assess the extent and nature of the missing data first. If the missing data is minimal and random, I might exclude those records. However, if a significant portion is missing, I would consider imputation methods, such as using the mean or median, or employing more advanced techniques like multiple imputation to maintain the integrity of the dataset.”

SQL and Data Management

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

This question tests your SQL knowledge, which is essential for a Data Analyst role.

How to Answer

Define both types of joins and provide a scenario where each would be applicable.

Example

“An INNER JOIN returns only the rows that have matching values in both tables, while a LEFT JOIN returns all rows from the left table and the matched rows from the right table. For example, if I want to list all customers and their transactions, I would use a LEFT JOIN to ensure I include customers who have not made any transactions.”

2. How would you optimize a slow-running SQL query?

This question assesses your problem-solving skills in data management.

How to Answer

Discuss various strategies for query optimization, such as indexing, query restructuring, or analyzing execution plans.

Example

“I would start by examining the execution plan to identify bottlenecks. If I notice that certain columns are frequently queried, I would consider adding indexes. Additionally, I would look for opportunities to simplify the query or reduce the number of joins to improve performance.”

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

This question allows you to demonstrate your SQL proficiency and analytical skills.

How to Answer

Provide a specific example of a complex query, explaining its components and the insights it provided.

Example

“I wrote a complex SQL query to analyze customer transaction patterns over the last year. The query involved multiple joins across customer, transaction, and product tables, along with window functions to calculate running totals. This analysis helped identify trends in customer spending, which informed our marketing strategies.”

4. What are window functions in SQL, and how have you used them?

This question tests your advanced SQL knowledge.

How to Answer

Explain what window functions are and provide an example of their application.

Example

“Window functions perform calculations across a set of table rows related to the current row. I used window functions to calculate moving averages for customer transactions, which allowed us to smooth out fluctuations and better understand long-term trends in spending behavior.”

5. How do you ensure data quality in your analyses?

This question assesses your approach to maintaining data integrity.

How to Answer

Discuss the steps you take to validate and clean data before analysis.

Example

“I ensure data quality by implementing a multi-step validation process. This includes checking for duplicates, verifying data types, and conducting consistency checks against known benchmarks. Additionally, I document any data cleaning steps taken to maintain transparency and reproducibility in my analyses.”

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: What's the time complexity?

• Write a function to find the maximum number in a list of integers. Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

• Write a query to get the top 3 highest employee salaries by department. Given the employees and departments table, write a query to get the top 3 highest employee salaries by department. The output should include the full name of the employee, the department name, and the salary, sorted by department name in ascending order and salary in descending order.

• Write a function to combine sorted integer lists into one sorted list. Given a list of sorted integer lists, write a function sort_lists to create a combined list while maintaining sorted order without importing any libraries or using the 'sort' or 'sorted' functions in Python.

• Write a function to swap nodes in a singly linked list. Given the head of a singly linked list represented as a ListNode, and two zero-indexed positions x and y, write a function swap_node which swaps the positions of nodes x and y and returns the new head. Note that you cannot simply swap the values of these nodes; you must swap these using pointer manipulation.

• How would you investigate a decrease in credit card payment amounts per transaction? You work for a financial company and notice that the credit card payment amount per transaction has decreased. How would you investigate the cause of this change?

• How would you build a strategy to find the best small businesses to partner with? You are a credit card company looking to partner with more merchants. You have 100K small businesses to reach out to but can only contact 1000. How would you strategize to identify the best businesses to approach?

• What features would you include in a model to predict pizza order no-shows? Imagine you run a pizza franchise and face a problem with many no-shows after customers place their orders. What features would you include in a model to predict these no-shows?

• How does random forest generate the forest and why use it over logistic regression? Explain how random forest generates the forest. Additionally, why would we use random forest over other algorithms such as logistic regression?

• How would you build a fraud detection model with a text messaging service for a bank? You work at a bank that wants to build a model to detect fraud on the platform. The bank also wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction, allowing the customer to approve or deny the transaction with a text response. How would you build this model?

• What is the relationship between PCA and K-means clustering? Explain the relationship between Principal Component Analysis (PCA) and K-means clustering.

If you want more insights about the company, check out our main Old National Bank 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 Old National Bank'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 Old National Bank 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!