Flexshopper is a dynamic fintech company that offers a unique lease-to-own marketplace catering to both consumers and retailers. With a focus on flexibility and accessibility, Flexshopper has made it easier for customers to acquire the products they need through flexible payment plans.

Stepping into the role of a Growth Marketing Analyst at Flexshopper is an exciting opportunity to shape the company's market presence and growth strategies. The position requires a deep understanding of data analytics, marketing strategies, and consumer behavior. As a Growth Marketing Analyst, you'll work on optimizing marketing campaigns, leveraging data insights to drive user acquisition, and ultimately contributing to the company's overall growth.

If you're considering applying for this role, our guide on Interview Query is your go-to resource. We provide an in-depth look at the interview process, commonly asked questions, and essential tips to help you succeed. Let's dive in!

Submitting Your Application

The first step is to submit a compelling application that reflects your skills and interest in joining Flexshopper as a Growth Marketing Analyst. Whether you were contacted by a Flexshopper recruiter or have taken the initiative yourself, carefully review the job description and tailor your resume according to the prerequisites.

Tailoring your resume may include identifying specific keywords that the hiring manager might use to filter résumés 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 resume 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 Growth Marketing Analyst hiring manager could be 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 Growth Marketing Analyst role is usually conducted through virtual means, including video conferencing and screen sharing. Questions in this 1-hour long interview stage may revolve around Flexshopper’s marketing strategies, data analytics, and campaign performance metrics.

In the case of marketing analytics roles, take-home assignments regarding market analysis, data visualization, and digital marketing strategies are incorporated. Apart from these, your proficiency with marketing tools, hypothesis testing, and data interpretation 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

Following 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 data analytics and campaign strategy 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 Growth Marketing Analyst role at Flexshopper.

Quick Tips For Flexshopper Growth Marketing Analyst Interviews

• Understand Flexshopper’s Core Values: Flexshopper values customer satisfaction and innovative marketing solutions. Make sure to study their mission statement and reflect their values in your responses.
• Be Data-Oriented: Flexshopper’s interviews assess your ability to derive actionable insights from data. Brush up on your knowledge of data analytics, market analysis, and relevant marketing metrics.
• Prepare for Behavioral Questions: Expect a good mix of technical and behavioral questions. Practice answering questions that highlight your problem-solving skills and experiences with past marketing campaigns.

Typically, interviews at Flexshopper vary by role and team, but commonly Growth Marketing 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 card for the company.

• 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 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 and describe scenarios where bagging is preferred over boosting. Provide examples of the tradeoffs between the two, 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 installment payments.

• 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.

What is the average salary for a Growth Marketing Analyst at Flexshopper?

Q: What is the role of a Growth Marketing Analyst at Flexshopper? A: The Growth Marketing Analyst at Flexshopper plays a crucial role in driving the company's growth through data-driven marketing strategies. Responsibilities include analyzing marketing data, identifying growth opportunities, optimizing marketing campaigns, and collaborating with various teams to implement data-backed decisions.

Q: What qualifications are required for the Growth Marketing Analyst position at Flexshopper? A: Ideal candidates should possess a background in marketing, statistics, or a related field, with strong analytical skills. Proficiency in data analysis tools such as SQL, Excel, and Google Analytics is essential. Experience with A/B testing, marketing automation platforms, and knowledge of the e-commerce industry are highly advantageous.

Q: Can you describe the company culture at Flexshopper? A: Flexshopper fosters a dynamic and inclusive work environment that values innovation, collaboration, and continuous learning. Employees are encouraged to take initiative, share ideas, and contribute to the company's growth. The company places a strong emphasis on work-life balance and professional development.

Q: What is the interview process like for the Growth Marketing Analyst position at Flexshopper? A: The interview process typically includes an initial phone screen with a recruiter, followed by a technical interview to assess analytical skills and marketing knowledge. This may be followed by on-site or virtual interviews with team members to evaluate cultural fit and problem-solving abilities. Candidates may also be asked to complete a case study or practical assignment.

Q: How can I best prepare for an interview at Flexshopper for the Growth Marketing Analyst position? A: To prepare for an interview at Flexshopper, research the company thoroughly, review the job description, and understand the required skills. Brush up on your data analysis and marketing knowledge, and practice answering common interview questions. Utilize resources like Interview Query to practice and refine your technical and problem-solving skills.

Embarking on a career as a Growth Marketing Analyst at Flexshopper could be transformative, offering a dynamic work environment filled with opportunities to drive significant impact. 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 machine learning engineer interview questions and challenges.

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!