Arvest Bank, headquartered in Bentonville, Arkansas, is renowned for its community-focused banking approach and innovative financial solutions. With over a hundred years of history and more than 270 bank branches, Arvest has positioned itself as a solid pillar in the banking industry.

Joining Arvest Bank as a Data Scientist involves delving into a myriad of responsibilities that require a proficient understanding of data analysis, statistical modeling, and machine learning algorithms. The role is pivotal for informing strategic business decisions through the development and implementation of data-driven insights.

This guide will equip you with crucial knowledge about the interview process for a Data Scientist role at Arvest Bank, including the nature of commonly asked questions, and key interview tips. Ready to step into the world of Arvest Bank? Let’s dive into the details and help you prepare for a successful interview journey with Interview Query!

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 Data Scientist. 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 data scientist 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 data scientist 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 data scientist roles, take-home assignments regarding product metrics, analytics, and data visualization may be incorporated. Apart from these, your proficiency in hypothesis testing, probability distributions, and machine learning fundamentals 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 programming and ML modeling 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 data scientist role at Arvest Bank.

Quick Tips For Arvest Bank Data Scientist Interviews

• Understand Arvest Bank’s Domain: Familiarize yourself with the banking and financial services industry, especially focusing on the specific needs and challenges faced by Arvest Bank. Knowing the context can help you frame your technical answers better.
• Brush Up on Machine Learning: Core machine learning concepts and their applications in financial services will likely come up during the interview. Make sure you are comfortable discussing algorithms, their advantages, and their limitations.
• Practice Behavioral Questions: Arvest Bank values cultural fit and teamwork. Use the STAR method (Situation, Task, Action, Result) to prepare for behavioral questions and highlight your collaborative skills and problem-solving abilities.

Typically, interviews at Arvest Bank vary by role and team, but commonly Data Scientist 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. If the department contains less than 3 employees, list the top 2 or top 1 highest salaries. The output should include the full name of the employee in one column, the department name, and the salary. The output should be 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 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 Scientist at Arvest Bank?

Q: What is the interview process like for a Data Scientist position at Arvest Bank?

A: The interview process at Arvest Bank generally involves a recruiter call, technical assessments, and multiple rounds of interviews. These stages assess your technical skills, problem-solving abilities, and cultural fit with the bank’s values.

Q: What are some typical responsibilities of a Data Scientist at Arvest Bank?

A: As a Data Scientist at Arvest Bank, your responsibilities will include analyzing large datasets, developing predictive models, optimizing business processes, and collaborating with various teams to drive data-driven decision making.

Q: What skills are essential for a Data Scientist role at Arvest Bank?

A: Key skills for this role include proficiency in programming languages such as Python or R, strong statistical and machine learning knowledge, experience with data visualization tools, and excellent communication skills.

Q: Does Arvest Bank promote professional development for Data Scientists?

A: Yes, Arvest Bank encourages continuous learning and professional growth. They provide opportunities for training, attending conferences, and access to resources like Interview Query to help you sharpen your skills.

Q: What is the company culture like at Arvest Bank?

A: Arvest Bank boasts a collaborative, inclusive, and community-focused culture. Employees are encouraged to innovate, share ideas, and contribute to impactful projects on both local and national scales.

Landing a Data Scientist position at Arvest Bank is a promising opportunity to delve into a challenging and impactful role within a dynamic financial institution. To ace your interview, preparation is key. Explore our detailed Arvest Bank Interview Guide for insights on what to expect. We've also created interview guides for other roles like software engineer and data analyst, helping you understand Arvest Bank's diverse interview landscape.

At Interview Query, we provide a comprehensive toolkit to enhance your interview skills and boost your confidence, empowering you to tackle the most challenging questions with strategic insight. Check out our company interview guides for extensive preparation tips. If you have any questions, feel free to reach out. Good luck with your interview!