Arvest Bank stands as a prominent financial institution offering a comprehensive suite of banking and wealth management services. Known for its commitment to community and customer service, Arvest boasts a robust presence with over 200 branches across the Midwest and Southern United States.

Embarking on a career with Arvest Bank as a Business Intelligence professional entails playing a crucial role in shaping the bank’s data-driven strategies. This position demands proficiency in data analysis, SQL, and data visualization tools. The role involves transforming raw data into actionable insights that inform business decisions, drive growth, and enhance operational efficiency.

If you aspire to join Arvest's dynamic team, our guide on Interview Query is designed to assist you through the interview journey. We will provide insights into the interview process, share frequently asked questions, and offer tips to help you succeed. Let’s navigate your path to a potential career at Arvest Bank!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Arvest Bank as a Business Intelligence professional. Whether you were contacted by an Arvest Bank recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Arvest Bank Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Arvest Bank Business Intelligence hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Arvest Bank Business Intelligence role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Arvest Bank’s data systems, ETL pipelines, and SQL queries.

In the case of Business Intelligence roles, take-home assignments regarding data visualization, building dashboards, and translating business requirements into technical solutions are incorporated. Apart from these, your proficiency in data modeling, report generation, and analytics may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Arvest Bank office. Your technical prowess, including data manipulation and BI tool utilization capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Business Intelligence role at Arvest Bank.

Quick Tips For Arvest Bank Business Intelligence Interviews

• Understand Financial Services: Arvest Bank is deeply embedded in the financial services industry. Familiarize yourself with industry-specific data challenges and Arvest-specific products or services.
• Proficiency in BI Tools: Make sure to brush up on your expertise with common BI tools like Tableau, Power BI, or Looker. Practice creating dashboards and visualizations that can deliver key business insights.
• Strong Analytical Skills: Data-driven decision making is crucial in this role. Prepare to discuss instances where you provided actionable insights based on your analysis and how it benefited the business.

Typically, interviews at Arvest Bank vary by role and team, but commonly Business Intelligence 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 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. 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 decrease?

• 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 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.

Are you ready to embark on an exciting career journey with Arvest Bank as a Business Intelligence professional? Dive into our Arvest Bank Interview Guide to uncover key insights and prepare for the questions that could be asked. We’ve meticulously crafted guides for various roles, such as software engineer and data analyst, to give you a comprehensive understanding of Arvest Bank’s interview process.

At Interview Query, we’re dedicated to equipping you with the ultimate toolkit of knowledge, confidence, and strategic guidance to excel in every interview challenge at Arvest Bank. Explore all our company interview guides for better preparation, and feel free to reach out to us with any questions.

Good luck with your interview!