Techstar Group is a global digital solutions and professional services firm committed to empowering businesses by leveraging emerging technologies. We deliver cutting-edge solutions with agility, responsiveness, transparency, and integrity. As a Data Analyst at Techstar Group, you'll utilize computer-based systems to analyze and improve supplier-related data and performance. You will play a crucial role in coordinating feasibility meetings, managing quality data, generating reports, and supporting the implementation of new data systems. A strong understanding of data analytics, supplier improvement, and automotive manufacturing processes, along with proficiency in tools like MS Excel, PowerPoint, Access, and programming capabilities, are essential. If you're ready to bring your skills to a dynamic and innovative environment, this guide by Interview Query will walk you through the interview process and help you prepare effectively. Let's get started!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Techstar Group as a data analyst. Whether you were contacted by a Techstar 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 Techstar 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 Techstar data analyst hiring manager may be 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 Techstar data analyst role usually is conducted through virtual means, including video conferences and screen sharing. Questions in this 1-hour long interview stage may revolve around Techstar’s data systems, ETL pipelines, and SQL queries.

For data analyst roles, take-home assignments regarding product metrics, analytics, and data visualization are also incorporated. Apart from these, your proficiency with 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

After 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 Techstar office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated among 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 Techstar.

Quick Tips For Techstar Group 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 Techstar interview include:

• Understand Data Systems Used in Techstar: Techstar’s questions are often standardized and may involve their specific data systems and workflows. Familiarize yourself with the specific systems mentioned in the job description, such as SharePoint, Salesforce, and Excel.

• Showcase Data-Driven Decision Making: Techstar’s data science interviews assess how well you can provide business-driving insights with data science. Brush up your knowledge of statistics and probability as these questions can be some of the hardest to solve.

• Highlight Cross-Functional Collaboration: Techstar emphasizes team-focused process planning and execution. Be prepared to provide examples of your experience working cross-functionally and your ability to manage multiple projects at once.

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

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function to find the maximum number in a list of integers. Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

• Create a function convert_to_bst to convert a sorted list into a balanced binary tree. Given a sorted list, create a function convert_to_bst that converts the list into a balanced binary tree. The output binary tree should be balanced, meaning the height difference between the left and right subtree of all the nodes should be at most one.

• Write a function to simulate drawing balls from a jar. Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named jar, with corresponding counts of the balls stored in the same index in a list called n_balls.

• Develop a function can_shift to determine if one string can be shifted to become another. Given two strings A and B, write a function can_shift to return whether or not A can be shifted some number of places to get B.

• What are the drawbacks of having student test scores organized in the given layouts? Assume you have data on student test scores in two different layouts. Identify the drawbacks of these layouts and suggest formatting changes to make the data more useful for analysis. Additionally, describe common problems seen in "messy" datasets.

• How would you figure out where the mouse is using the fewest number of scans? You have a 4x4 grid with a mouse trapped in one of the cells. You can only scan subsets of cells to know if the mouse is within that subset. Devise a strategy to locate the mouse using the fewest scans.

• How would you decide which Dashers do deliveries in NYC and Charlotte for Doordash? Doordash is launching delivery services in New York City and Charlotte. Develop a process for selecting dashers (delivery drivers) and determine if the criteria for selection should be the same for both cities.

• What factors could have biased Jetco's study on boarding times? Jetco, a new airline, was found to have the fastest average boarding times in a study. Identify potential factors that could have biased this result and what you would investigate further.

• How would you design an A/B test to evaluate a pricing increase for a B2B SAAS company? You work at a B2B SAAS company interested in testing different subscription pricing levels. Design a two-week-long A/B test to evaluate a pricing increase and determine if it is a good business decision.

• How much should a ride-sharing app budget for a $5 coupon initiative? A ride-sharing app has a probability (p) of dispensing a $5 coupon to a rider and services (N) riders. Calculate the total budget needed for the coupon initiative.

• What is the probability of riders getting a coupon? A driver using the app picks up two passengers. Determine:

• The probability of both riders getting the coupon.

• The probability that only one of them will get the coupon.

• What is a confidence interval for a statistic and why is it useful? Explain what a confidence interval is, why it is useful to know the confidence interval for a statistic, and how to calculate it.

• What is the probability that item X is found on Amazon's website? Amazon has a warehouse system where items are located at different distribution centers. In one city, the probabilities that item X is available at warehouse A or B are 0.6 and 0.8, respectively. Calculate the probability that item X would be found on Amazon's website.

• Is a coin fair if it comes up tails 8 times out of 10 flips? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if this coin is fair.

• What are time series models and why are they needed? Describe what time series models are and explain why they are necessary when less complicated regression models exist.

• How would you justify the complexity of building a neural network model and explain predictions to non-technical stakeholders? Your manager asks you to build a neural network model to solve a business problem. How would you justify the complexity of the model and explain its predictions to non-technical stakeholders?

• How would you evaluate and deploy 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, and how would you assess its performance before and after deployment?

• How does random forest generate the forest, and why use it over logistic regression? Explain how random forest generates its forest of trees. Additionally, why would you choose random forest over other algorithms like logistic regression?

• How would you explain linear regression to a child, a first-year college student, and a seasoned mathematician? Explain the concept of linear regression to three different audiences: a child, a first-year college student, and a seasoned mathematician, tailoring your explanations to their understanding levels.

• What are the key differences between classification models and regression models? Describe the main differences between classification models and regression models.

What is the average salary for a Data Analyst at Techstar Group?

Q: What does the Data Analyst position at Techstar Group entail?
The Data Analyst role involves coordinating, monitoring, tracking, and reporting supplier-related details and performance. You will analyze data, recommend improvements, and support various data management solutions. You'll also oversee quality files, change management, and generate quality scorecard reports.

Q: What skills and qualifications are required for the Data Analyst position?
To qualify, you need a Bachelor’s degree in finance, Business, IT or a related field or equivalent job training. You should have at least 3 years of professional experience, extensive knowledge of MS Excel, PowerPoint, Access, and some programming capabilities. Strong initiative, time management skills, and a thorough understanding of data analytics are essential.

Q: What is the company culture at Techstar Group like?
Techstar Group prides itself on a culture of agility, responsiveness, transparency, and integrity. We leverage emerging technologies to deliver cutting-edge solutions for our clients, and team collaboration is a crucial aspect of our work environment.

Q: How can I prepare for an interview at Techstar Group?
Research the company, review your technical skills, and practice common interview questions through Interview Query. Be prepared to discuss your past experiences and how they relate to the responsibilities of the Data Analyst position. Familiarity with automotive manufacturing processes can also be beneficial.

Q: What kind of projects will I work on at Techstar Group?
You'll be involved in coordinating supplier training activities, feasibility meetings for site changes, updating Monthly Management Reports, and other cross-functional team activities. Your role will also include implementing new data systems to improve departmental efficiencies.

Interested in joining Techstar Group as a Data Analyst? Check out our main Techstar Group Interview Guide for detailed insights into potential interview questions that might come your way. Our platform has also created comprehensive interview guides for other roles such as software engineer and data analyst, so you can get the lowdown on what to expect in any position.

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 Techstar Group interview question and challenge.

Explore all our company interview guides for better preparation. If you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!