Global Lending Services LLC is a prominent financial services company that specializes in auto lending solutions. Renowned for its customer-centric approach and innovative lending programs, GLS offers a dynamic work environment committed to growth and development.

As a Data Analyst at GLS, you will play a critical role in dissecting complex data sets, optimizing performance metrics, and generating actionable insights to drive business strategies. Your responsibilities will include data mining, statistical analysis, and building predictive models.

In this guide, we’ll walk you through the GLS Data Analyst interview process, share commonly asked questions, and provide useful tips to help you prepare. Let’s get started with Interview Query!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Global Lending Services Llc as a Data Analyst. Whether you were contacted by a recruiter from Global Lending Services Llc 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 Global Lending Services Llc 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 hiring manager for the Data Analyst position at Global Lending Services Llc stays present during the screening round to answer your queries about the role and the company itself. They may also engage 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 Data Analyst role at Global Lending Services Llc is usually conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Global Lending Services' 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 fundamentals of machine learning 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

Once you pass the technical virtual interview, a follow-up call with the recruiter outlining the next stage will take place, inviting you to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Global Lending Services Llc office. Your technical prowess, including programming and analytics 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 Global Lending Services Llc.

Quick Tips For Global Lending Services Llc Data Analyst Interviews

• Master SQL and Data Systems: Make sure to have a thorough understanding of SQL and the data systems used by Global Lending Services Llc. Technical questions revolving around ETL pipelines and database management are common.
• Prepare for Metrics and Visualization Challenges: The role demands strong product metrics and data visualization skills. Ensure to practice case studies and real-scenario problems that measure your ability to derive insights from data.
• Showcase Business Acumen: Global Lending Services Llc values data-driven insights that drive business decisions. Brush up on your knowledge of business analytics and how data solutions impact various business operations.

Typically, interviews at Global Lending Services Llc 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-tests 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 to improve usability 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 the value of each marketing channel.

• 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 investigate if an email campaign led to increased conversion rates? Analyze a scenario where a new email campaign coincides with an increase in conversion rates. Determine if the campaign caused the increase or if other factors were involved.

• 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 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 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 two machine learning algorithms. Describe scenarios where bagging (e.g., Random Forest) is preferred for reducing variance and boosting (e.g., AdaBoost) is preferred for reducing bias. Provide examples of tradeoffs between the two.

• 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 differences between Lasso and Ridge Regression, focusing on their regularization techniques. Highlight how Lasso performs feature selection by shrinking coefficients to zero, while Ridge penalizes large coefficients without eliminating features.

• What are the key differences between classification models and regression models? Describe the main differences between classification and regression models. Classification models predict categorical outcomes, while regression models predict continuous outcomes. Discuss examples and use cases for each type.

What is the average salary for a Data Analyst at Global Lending Services Llc?

Q: What does the interview process at Global Lending Services LLC for a Data Analyst position involve?

A: The interview process at Global Lending Services LLC typically involves several rounds, including an initial recruiter call, a technical assessment, and an onsite interview. The process is designed to evaluate your analytical skills, technical expertise, and cultural fit within the company.

Q: What are the key responsibilities of a Data Analyst at Global Lending Services LLC?

A: As a Data Analyst at Global Lending Services LLC, your responsibilities will include analyzing complex data sets, creating detailed reports, and providing actionable insights to drive business decisions. You will also work closely with different teams to identify trends and optimize processes.

Q: What skills are necessary to succeed as a Data Analyst at Global Lending Services LLC?

A: To succeed in this role, you should have strong analytical skills, proficiency in SQL, Excel, and other data manipulation tools, as well as experience with data visualization tools like Tableau. Excellent communication skills are also vital to translate complex data into actionable insights.

Q: What is the company culture like at Global Lending Services LLC?

A: Global Lending Services LLC fosters a collaborative, inclusive, and dynamic work environment. The company values innovation, continuous learning, and teamwork, aiming to create a positive impact both within the organization and in the financial services industry.

Q: How can I best prepare for an interview at Global Lending Services LLC?

A: To prepare for an interview at Global Lending Services LLC, research the company's services and industry trends, practice common interview questions on Interview Query, and refine your technical skills, particularly in data analysis and visualization. Be ready to discuss your past projects and how they align with the role you're applying for.

If you want more insights about the company, check out our main Global Lending Services 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 Global Lending Services’ 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 Global Lending Services 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!