Gametime United is revolutionizing the live event experience by connecting fans through shared, once-in-a-lifetime moments. With platforms across iOS, Android, mobile web, and desktop, Gametime is reshaping event ticketing in the US and Canada.

As a Data Analyst at Gametime, you will collaborate with various departments to solve critical business challenges. Your role will involve analyzing user behavior, providing insights for business decisions, and maintaining business intelligence reporting. Ideal candidates are adaptable, data-driven, and proficient in SQL, with a strong understanding of statistical analysis and a knack for problem-solving.

In this guide, we will explore the interview process, typical Data Analyst interview questions, and offer valuable tips to enhance your preparation. Welcome to Interview Query's comprehensive resource for aspiring Gametime Data Analysts!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Gametime United as a data analyst. Whether you were contacted by a Gametime 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 Gametime’s 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 Gametime 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 Gametime 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 Gametime’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 Gametime’s 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 Gametime.

Quick Tips For Gametime United Data Analyst Interviews

• Understand Gametime’s Products: Gametime’s interview questions may focus on situational scenarios with their products. Study Gametime’s platform and events to understand how you would personally improve or analyze them.

• Be Data-Driven: Gametime’s data analyst interviews assess how well you can provide business-driving insights with your analysis. Brush up on your SQL and statistical analysis skills given these questions can be some of the hardest to solve.

• Show Passion for Live Experiences: Gametime values the spirit of shared live experiences. Practice responding to behavioral questions with answers that touch on Gametime’s mission to unite the world through these experiences.

Typically, interviews at Gametime United vary by role and team, but commonly Data Analyst interviews follow a fairly standardized process across these question topics.

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to someone without a technical background.

• Write a function to simulate coin tosses with a given probability of heads. Create a function that takes the number of tosses and the probability of heads as inputs and returns a list of 'H' or 'T' representing the outcomes of the coin tosses.

• How much do you expect to pay for a sports game ticket considering the risk of a scalped ticket not working? Calculate the expected cost of attending the game, considering the 20% chance that a $50 scalped ticket might not work and the need to buy a $70 box office ticket if it fails.

• What is the probability of drawing three cards in increasing order from a shuffled deck of 500 cards? Determine the probability that each subsequent card drawn from a shuffled deck of 500 cards will be larger than the previous one.

• How do you calculate the average lifetime value for a SAAS company with given metrics? Given a product cost of $100 per month, a 10% monthly churn rate, and an average customer lifespan of 3.5 months, calculate the formula for the average lifetime value.

• What metrics would you use to determine the value of each marketing channel? Given all the different marketing channels and their respective costs at Mode, a B2B analytics dashboard company, what metrics would you use to evaluate the value of each marketing channel?

• What would you do if friend requests are down 10% on Facebook? A product manager at Facebook informs you that friend requests have decreased by 10%. What steps would you take to address this issue?

• How would you improve Google Maps and measure the success of your improvements? As a PM on Google Maps, how would you improve the application? What metrics would you use to evaluate the success of your feature improvements?

• How do you calculate the average lifetime value for a SAAS company? For a SAAS company with a product costing $100 per month, a 10% monthly churn rate, and an average customer lifespan of 3.5 months, how would you calculate the average lifetime value?

• How would you analyze the churn behavior of Netflix users on different pricing plans? Netflix has two pricing plans: $15/month or $100/year. An executive wants an analysis of the churn behavior of users on these plans. What metrics, graphs, or models would you use to provide an overarching view of subscription performance?

• Write a Python program to check if each string in a list has all the same characters. Given a list of strings, write a Python program to check whether each string has all the same characters or not. Determine the complexity of this program.

• Write a function to determine if a string is a palindrome. Given a string, write a function to determine if it is a palindrome or not. A palindrome reads the same forwards and backwards.

• Create a function to simulate coin tosses based on a given probability of heads. Write a function that takes the number of tosses and a probability of heads as input and returns a list of randomly generated results representing the outcomes of coin tosses.

• Develop a function to perform bootstrap sampling and calculate a confidence interval. Given an array of numerical values, bootstrap samples, and size for a confidence interval, write a function to perform bootstrap sampling and calculate the confidence interval.

• Write a program to determine the term frequency (TF) values for each term in a document. Given a text document in the form of a string, write a program in Python to determine the term frequency (TF) values for each term in the document. Round the term frequency to 2 decimal points.

• What metrics would you use to track accuracy and validity of a spam classifier model? Assume you have built a V1 of a spam classifier for emails. What metrics would you use to track the model's accuracy and validity?

• How would you evaluate the suitability and performance of a decision tree model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will repay a personal loan. How would you evaluate if a decision tree is the correct model? If you proceed with it, how would you evaluate its performance before and after deployment?

• What is Linear Discriminant Analysis (LDA) in machine learning and its use cases? Explain the concept of Linear Discriminant Analysis (LDA) in machine learning. What are some practical use cases for LDA?

• How would you collect and aggregate unstructured video data for an ETL pipeline? You are designing an ETL pipeline for a model that uses videos as input. How would you collect and aggregate multimedia information, specifically unstructured data from videos?

• How would you determine which search engine performs better and which metrics to track? You are working on building a better search engine for Google. After building it, how would you determine if it serves better results than the existing one in production? What metrics would you track?

What is the average salary for a Data Analyst at Gametime United?

Q: What does Gametime United do?

Gametime United focuses on uniting people through live experiences. We provide an extraordinary platform for discovering, purchasing, and enjoying last-minute tickets to events across the US and Canada via iOS, Android, mobile web, and desktop.

Q: What are the primary responsibilities of the Data Analyst role at Gametime United?

As a Data Analyst at Gametime United, you will work cross-functionally with various teams to solve business-critical issues. You'll analyze user behavior data, maintain and improve our business intelligence reporting, and generate insights for product and feature improvements.

Q: What skills and experience are ideal for the Data Analyst position?

The ideal candidate should have 1-3+ years of Data Analyst experience, proficiency in SQL, experience with user-centric products, and knowledge of statistical analysis. Experience with A/B testing, Python or R, and data visualization software is a plus.

Q: What benefits does Gametime United offer?

Gametime United offers a range of benefits including flexible PTO, medical, dental, and vision insurance, life insurance, disability benefits, 401K, HSA, pre-tax savings programs, new equipment setup, wellness programs, and tenure recognition.

Q: How can I prepare for an interview with Gametime United?

To prepare for an interview, research the company and its mission. Practice relevant technical questions using platforms like Interview Query, and be ready to discuss your past experiences and how they relate to the responsibilities and skills outlined for the Data Analyst position.

At Gametime United, we believe live experiences bring us together, bridging today's social and digital divides by focusing on shared, once-in-a-lifetime moments. Our mission is to unite the world through these experiences, offering fans an exceptional platform for discovering and purchasing last-minute tickets to events across the U.S. and Canada. As a Data Analyst, you will be key in driving our vision forward by using your analytical skills to influence critical business decisions and improve our product offerings. If you are data-driven, organized, and thrive in a fast-paced environment, this is the perfect opportunity for you. Dive deeper into the specifics of this role and get prepared with our main Gametime United Interview Guide. At Interview Query, we equip you with all the tools and insights needed to excel in every aspect of your interview process. Good luck with your interview!