FlexShopper is a growing innovative FinTech and eCommerce company headquartered in Boca Raton, Florida, that offers brand name durable goods to consumers on a lease-to-own (LTO) basis through its ecommerce marketplace and LTO payment methods. As a Business Analyst at FlexShopper, you will play a vital role in ensuring the stability, security, and success of our financial products and services. You'll work in a fast-paced, fluid environment, collaborating closely with cross-functional teams to analyze risk factors, develop underwriting strategies, and implement robust risk management procedures. This guide on Interview Query will walk you through the interview process, provide common Business Analyst interview questions, and offer valuable tips to help you succeed. Let's begin your journey to joining the FlexShopper team!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Flexshopper as a Business Analyst. Whether you were contacted by a Flexshopper 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 Flexshopper 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 Flexshopper Business Analyst 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 Flexshopper Business Analyst role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Flexshopper’s data systems, risk assessment methodologies, and SQL queries.

In the case of Business Analyst roles, take-home assignments regarding product metrics, analytics, and process flow analysis are incorporated. Apart from these, your proficiency against risk management, quantitative analysis, and project management 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 Flexshopper office. Your technical prowess, including risk management and process optimization, 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 Analyst role at Flexshopper.

Quick Tips For Flexshopper Business Analyst Interviews

• Preparation for this role should involve understanding Flexshopper’s unique business model, especially its lease-to-own (LTO) aspect.
• Brush up on your technical skills, particularly related to risk engineering, SQL, and project management tools like Jira and Confluence.
• Showcase your ability to communicate complex technical information clearly and effectively to diverse stakeholders.

Ready to prepare for your interview? Visit Interview Query for comprehensive interviewing guides and practice resources.

Typically, interviews at Flexshopper vary by role and team, but commonly Business Analyst 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, and specify scenarios for using one 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 improvements, and describe common issues in "messy" datasets.

• What metrics would you use to determine the value of each marketing channel? Given data on marketing channels and costs for a B2B analytics dashboard company, identify key metrics to evaluate the value of each channel.

• How would you determine the next partner card for a company 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 investigate if a redesigned email campaign led to an increase in conversion rates? Analyze whether a new email journey caused an increase in conversion rates, considering previous trends and 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 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 and describe scenarios where bagging is preferred over boosting. Provide examples of the tradeoffs, such as variance reduction in bagging and bias reduction in boosting.

• How would you evaluate and compare two credit risk models for personal loans?

• Identify the type of model developed by the co-worker for loan approval.
• Describe how to measure the difference between two credit risk models over a timeframe, considering monthly installments.

• List the metrics to track for measuring the success of the new model, such as accuracy, precision, recall, and AUC-ROC.

• What’s the difference between Lasso and Ridge Regression? Explain the key 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? Describe the main differences between classification and regression models, including their objectives, output types, and common use cases.

Excited about a career in FinTech and eCommerce? Flexshopper, a pioneer in lease-to-own technology, offers an engaging workplace where your analytical skills can drive meaningful impact. As a Business Analyst at Flexshopper, you'll be at the heart of innovation, working closely with diverse teams to ensure successful project execution and improved business processes. With opportunities for personal growth, competitive benefits, and an inclusive work culture, Flexshopper is the ideal place to advance your career.

If you want more insights about the company, check out our main Flexshopper 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 Flexshopper’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 Flexshopper 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!