Arvest Bank is a prominent financial institution serving a wide footprint across Arkansas, Kansas, Missouri, and Oklahoma. Known for its steadfast commitment to providing comprehensive financial services, Arvest offers a full suite of benefits, including health, life, financial, and wellness options.

As a Data Analyst within Arvest's Consumer Lending Division, specifically the Marketing and Decision Analytics team, you'll play a critical role in driving business outcomes and enhancing customer experiences. You'll work with statistical programming languages, SQL, and relational databases. Ideal candidates should have at least one year of experience in financial services, consumer lending, or commercial and small business lending.

If you're eager to join Arvest Bank, this Interview Query guide will help you navigate the interview process, from understanding the essential job duties to preparing for commonly asked questions. Let's get started!

Submitting Your Application

The first step is to submit a compelling application that showcases your technical abilities and enthusiasm for joining Arvest Bank as a Data Analyst. Whether you were contacted by an Arvest recruiter or initiated the process yourself, thoroughly review the job description and tailor your CV to match the qualifications.

Tailoring your CV might include highlighting specific keywords from the job description and crafting a targeted cover letter. Additionally, emphasize relevant technical skills and past experiences related to data analysis, SQL, and financial services.

Recruiter/Hiring Manager Call Screening

Should your CV be shortlisted, a recruiter from the Arvest Talent Acquisition Team will reach out to verify key details about your experiences and skill level. During this call, you might face behavioral questions and surface-level technical queries.

In some instances, the hiring manager for the Data Analyst position may join this initial call to answer your questions about the role and the company itself. Expect the conversation to last around 30 minutes.

Technical Virtual Interview

Once you clear the recruiter screening, you will be invited for a technical interview. This stage is often conducted virtually through video conferencing and screen sharing tools. The interview typically lasts about an hour.

Questions during this stage will revolve around Arvest Bank’s data systems, SQL queries, and ETL pipelines. You might also be given take-home assignments focusing on product metrics, analytics, or data visualization. Additionally, your understanding of hypothesis testing, probability distributions, and basic machine learning principles may be assessed.

Depending on the role's seniority, you might also encounter case studies and real-world problem scenarios.

Onsite Interview Rounds

After successfully navigating the virtual technical interview, a recruiter will schedule you for the onsite interview rounds. These sessions will take place at an Arvest office and involve multiple interview rounds with different teams. Your technical capabilities, including SQL programming and data modeling skills, will be thoroughly evaluated.

If you were assigned any take-home exercises, a presentation might be part of your onsite interview to discuss your findings and recommendations.

Quick Tips For Arvest Bank Data Analyst Interviews

Here are three tips to help you prepare for an interview with Arvest Bank for the Data Analyst position:

• Understand Financial Services: Arvest Bank values experience in financial services, particularly in consumer lending and commercial lending products. Familiarize yourself with industry standards and Arvest's specific offerings to showcase your relevant knowledge.

• Master SQL and Data Visualization Tools: Strong proficiency in SQL and data visualization tools like Tableau is crucial for this role. Practice by solving SQL queries and creating dashboards that are both functional and visually appealing.

• Emphasize Analytical Skills: Be prepared to demonstrate your ability to gather, analyze, and present data effectively. This includes proving your skills in data mining, statistical analysis, and creating comprehensive reports to support business decisions.

Typically, interviews at Arvest Bank vary by role and team, but commonly Data Analyst interviews follow a fairly standardized process across these question topics.

• 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.

• 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 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 and two zero-indexed positions x and y, write a function swap_node to swap the positions of nodes x and y using pointer manipulation and return the new head.

• 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 build a strategy to identify the best businesses to reach out to?

• What features would you include in a model to predict a no-show for pizza orders? 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 predictive model to address this issue?

• How does random forest generate the forest, and why use it over logistic regression? Explain the process by which random forest generates its forest. Additionally, discuss why one might choose 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 its platform. The bank also wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction, allowing them to approve or deny the transaction via text response. How would you build this model?

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

What is the average salary for a Data Analyst at Arvest Bank?

Q: What does a Data Analyst at Arvest Bank do?

A: A Data Analyst at Arvest Bank supports business analytics and reporting initiatives in the Consumer Lending Division. This involves gathering and analyzing data, utilizing data discovery and mining techniques, and presenting findings to drive business outcomes and improve customer experiences. Key responsibilities include creating dashboards, maintaining reports, and using statistical programming languages and SQL.

Q: What qualifications are needed for the Data Analyst position at Arvest Bank?

A: Candidates should have a Bachelor’s Degree in Computer Science, Statistics, Operations Research, or a related field. At least 2 years of experience with statistical programming languages, SQL, and relational databases are required. Additionally, experience in customer or business analytics, data discovery, data modeling, ETL, and data cleansing is essential. Experience with financial services, banking, or lending products is preferred but not mandatory.

Q: Can I work remotely as an Arvest Bank Data Analyst?

A: Yes, the Data Analyst position can be located anywhere within Arvest’s 4-state footprint (AR, KS, MO, OK). However, the position requires availability Monday through Friday from 8 am to 5 pm, with the possibility of additional hours as needed.

Q: What benefits does Arvest Bank offer for the Data Analyst position?

A: Arvest Bank offers a comprehensive suite of benefits, which includes health and life insurance, financial and wellness benefits. For detailed information about the benefits, candidates can visit www.arvest.com/careers/benefits.

Q: How should I prepare for an interview for the Data Analyst role at Arvest Bank?

A: To prepare for the interview, research the company and its services, review your knowledge of SQL, statistical programming languages, and data analysis techniques. Practice common interview questions and be ready to discuss your past experiences and how they relate to the position. Leverage resources like Interview Query to practice and refine your interview skills.

If you're eager to embark on a meaningful career journey and drive impactful business outcomes at Arvest Bank, the Data Analyst position could be your next step. With competitive pay based on your experience and a comprehensive suite of benefits, you'll be well-equipped to make a difference. If you want more insights about the company, check out our main Arvest Bank Interview Guide, where we have covered many interview questions that could be asked.

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 Arvest Bank 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!