Popular Bank is a prominent financial institution known for its robust and customer-centric banking solutions. With a strong emphasis on innovation and growth, Popular Bank has cemented its position within the financial sector, continually improving its offerings to meet the evolving needs of its clients.
Joining Popular Bank as a Business Intelligence professional means contributing to data-driven decision-making processes that steer the bank's strategies and operations. This role requires proficiency in data extraction, analysis, visualization, and presenting actionable insights to stakeholders. The ideal candidate will possess strong analytical skills, familiarity with BI tools, and the ability to communicate complex data findings effectively.
At Interview Query, we aim to prepare you for every step of the interview journey with Popular Bank. Our guide covers the interview process, sample questions, and tips to help you succeed. Let’s dive in and get you ready for a successful interview!
The first step is to submit a compelling application that reflects your technical skills and interest in joining Popular Bank as a Business Intelligence professional. Whether you were contacted by a Popular 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.
If your CV happens to be among the shortlisted few, a recruiter from the Popular 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 Popular 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.
Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Popular Bank Business Intelligence role is usually conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Popular Bank’s data systems, ETL pipelines, and SQL queries.
In the case of Business Intelligence roles, take-home assignments regarding product metrics, analytics, and data visualization are incorporated. Apart from these, your proficiency against 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.
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 Popular Bank office. Your technical prowess, including programming and BI 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 Business Intelligence role at Popular Bank.
Quick Tips For Popular Bank Business Intelligence Interviews
A few tips for acing your Popular Bank interview include:
Typically, interviews at Popular Bank vary by role and team, but commonly Business Intelligence interviews follow a fairly standardized process across these question topics.
What are the Z and t-tests, and when should you use each? Explain the purpose and differences between Z and t-tests. Describe scenarios where one test is preferred over the other.
How would you reformat student test score data for better analysis? Given two datasets of student test scores, identify drawbacks in their current format. Suggest formatting changes and discuss common issues in "messy" datasets.
What metrics would you use to evaluate the value of marketing channels? Given data on marketing channels and costs for a B2B analytics dashboard company, identify key metrics to determine each channel's value.
How would you determine the next partner card using customer spending data? With access to customer spending data, outline a method to identify the best partner for a new credit card offering.
How would you verify if a redesigned email campaign increased conversion rates? Investigate whether a new email journey led to an increase in conversion rates, considering other potential influencing factors.
Write a function search_list
to check if a target value is in a linked list.
Write a function, search_list
, that returns a boolean indicating if the target
value is in the linked_list
or not. You receive the head of the linked list, which is a dictionary with keys value
and next
. If the linked list is empty, you'll receive None
.
Write a query to find users who placed less than 3 orders or ordered less than $500 worth of product.
Write a query to identify the names of users who placed less than 3 orders or ordered less than $500 worth of product. Use the transactions
, users
, and products
tables.
Create a function digit_accumulator
to sum every digit in a string representing a floating-point number.
You are given a string
that represents some floating-point number. Write a function, digit_accumulator
, that returns the sum of every digit in the string
.
Develop a function to parse the most frequent words used in poems.
You're hired by a literary newspaper to parse the most frequent words used in poems. Poems are given as a list of strings called sentences
. Return a dictionary of the frequency that words are used in the poem, processed as lowercase.
Write a function rectangle_overlap
to determine if two rectangles overlap.
You are given two rectangles a
and b
each defined by four ordered pairs denoting their corners on the x
, y
plane. Write a function rectangle_overlap
to determine whether or not they overlap. Return True
if so, and False
otherwise.
How would you design a function to detect anomalies in univariate and bivariate datasets? If given a univariate dataset, how would you design a function to detect anomalies? What if the data is bivariate?
What are the drawbacks of the given student test score data layouts? Assume you have data on student test scores in two layouts. What are the drawbacks of these layouts? What formatting changes would you make for better analysis? Describe common problems in “messy” datasets.
What is the expected churn rate in March for customers who bought subscriptions since January 1st? You noticed that 10% of customers who bought subscriptions in January 2020 canceled before February 1st. Assuming uniform new customer acquisition and a 20% month-over-month decrease in churn, what is the expected churn rate in March for all customers who bought the product since January 1st?
How would you explain a p-value to a non-technical person? How would you explain what a p-value is to someone who is not technical?
What are Z and t-tests, and when should you use each? What are the Z and t-tests? What are they used for? What is the difference between them? When should you use one over the other?
How does random forest generate the forest and why use it over logistic regression? Explain the process of how random forest generates multiple decision trees to form a forest. Discuss the advantages of using random forest over logistic regression, such as handling non-linear data and reducing overfitting.
When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. Describe scenarios where bagging is preferred over boosting and vice versa. Provide examples of the tradeoffs between the two methods.
What kind of model did the co-worker develop for loan approval? Identify the type of model used for determining loan approval based on customer inputs. Explain how to measure the difference between two credit risk models over time, considering personal loans are paid in monthly installments. List metrics to track the success of the new model.
What’s the difference between Lasso and Ridge Regression? Describe the differences between Lasso and Ridge Regression, focusing on their regularization techniques and how they handle feature selection and multicollinearity.
What are the key differences between classification models and regression models? Outline the main differences between classification and regression models, including their objectives, output types, and common use cases.
The interview process at Popular Bank generally consists of a phone interview with HR, a technical interview round, and a final onsite interview. These stages are designed to assess your analytical skills, problem-solving abilities, and suitability for the company culture.
Key skills for this position include strong familiarity with SQL, data analysis, ETL processes, data visualization tools like Tableau, and a good understanding of business metrics. Additionally, problem-solving and critical thinking are highly valued.
Expect questions that assess your proficiency with SQL queries, data modeling, and data warehousing. You might be given practical scenarios to solve, like optimizing a database query or creating a data pipeline. Review common interview questions on Interview Query to sharpen your skills.
Popular Bank values innovation, collaborative teamwork, and continuous learning. Employees appreciate the supportive atmosphere where they can grow professionally while contributing to impactful projects.
To prepare, thoroughly research Popular Bank and understand its business model. Practice problem-solving and technical questions on Interview Query. Review your technical skills and be ready to discuss how your previous experience and skills make you a great fit for the role.
Exploring a position at Popular Bank as a Business Intelligence professional offers a unique opportunity to leverage data in a dynamic environment. If you want more insights about the company, check out our main Popular 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 Popular 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 Popular Bank Business Intelligence 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!