FlexShopper, a subsidiary of FlexShopper Inc. (Nasdaq: FPAY), is a pioneering financial and technology company based in Boca Raton, Florida. Specializing in providing brand-name durable goods to consumers through a lease-to-own model, FlexShopper also offers LTO technology platforms to various retailers.

As a Data Analyst at FlexShopper, you will play a crucial role in a dynamic and inclusive fintech environment. You will manage, analyze, and interpret data to drive strategic decision-making. Reporting to the VP of Risk and Analytics, this full-time role requires collaboration within a fast-paced startup setting, focusing on quantitative data modeling, data visualization, and data management. Our comprehensive benefits package includes competitive compensation, health insurance, 401k match, and flexible work arrangements.

Explore this exciting opportunity to join a forward-thinking team at FlexShopper!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining FlexShopper as a Data 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 data 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 data 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, ETL pipelines, and SQL queries.

In the case of data analyst 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.

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 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 analyst role at FlexShopper.

Quick Tips For FlexShopper Data Analyst Interviews

• Should contain three tips for interviewing for this specific company based on interview experiences.

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your FlexShopper interview include:

• Understand FinTech Landscape: FlexShopper operates in the financial technology domain. Familiarize yourself with fundamental concepts, major industry players, and prevalent challenges in the fintech industry.
• Showcase Data Visualization Skills: The role emphasizes data visualization. Be prepared to discuss your experience with tools like PowerBI or Tableau and provide examples of how your visualizations have impacted business decisions.
• Highlight Risk Modeling Expertise: Risk modeling is a critical part of the role. Brush up on your quantitative modeling skills, and be ready to discuss your experience with machine learning models and statistical analysis.

Typically, interviews at Flexshopper vary by role and team, but commonly Data 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. 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 organization. Suggest formatting changes and discuss 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 a scenario where a new email campaign coincides with an increase in conversion rates. Determine if the increase is due to the campaign or other 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 (dataset 1 and dataset 2). 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 the product 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 how random forest creates multiple decision trees and combines their results. 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 the use cases for bagging and boosting algorithms. Provide examples of tradeoffs, such as bagging reducing variance and boosting improving accuracy but being more prone to overfitting.

• 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 metrics to track 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.

What is the average salary for a Data Analyst at Flexshopper?

FAQ for FlexShopper Data Analyst Position

Q: What does FlexShopper do? FlexShopper, LLC, is a financial and technology company that provides brand name durable goods to consumers on a lease-to-own (LTO) basis through its ecommerce marketplace and LTO payment method. Additionally, FlexShopper offers LTO technology platforms to retailers and e-tailers to facilitate transactions with consumers seeking durable goods without immediate available cash or credit.

Q: What are the key responsibilities of a Data Analyst at FlexShopper? A Data Analyst at FlexShopper is responsible for overseeing the collection, storage, and interpretation of data to support data-driven decision-making. The role includes quantitative data modeling, data visualization, and data collection and management. You will work closely with various multi-disciplinary teams to analyze risks, develop and maintain data models, and create visual reports for strategic decision-making.

Q: What qualifications and skills are required for the Data Analyst position? Candidates are required to have an undergraduate or graduate degree in a STEM discipline (Computer Science, Engineering, Mathematics, or Statistics). At least two years of experience in the financial industry is preferred. The role requires proficiency in analytical and statistical software (e.g., SAS, SQL, R, Python), strong communication skills, and experience with data visualization tools such as PowerBI or Tableau.

Q: What benefits does FlexShopper offer to its employees? FlexShopper offers a competitive benefits package including health insurance, vision, dental, and 401k with 100% employer match up to 4% with immediate vesting after 90 days. Employees enjoy 7 days of PTO after 6 months and 3 weeks after 1 year, optional disability and life insurance, pet insurance, flexible work arrangements, and company-sponsored gym memberships. There are also frequent rewards and recognition activities, a casual dress code, and free gourmet coffee/tea and snacks.

Q: What is the work environment like at FlexShopper? FlexShopper promotes a collaborative and dynamic work environment that is fast-paced and enjoyable, located in beautiful Boca Raton, Florida, or the stunning new offices in The Battery Atlanta. The company values a diverse and inclusive team culture, encourages creativity, and maintains a balance between work and life.

For aspiring data analysts with a passion for fintech and innovation, FlexShopper offers an unmissable opportunity. As a data analyst at FlexShopper, you will thrive in a dynamic and inclusive work environment while contributing to the company’s data-driven decision-making processes. This role calls for your expertise in data clustering, categorization, and visualization, empowering leadership with insightful analyses.

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 data analyst 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!