Tomtom is a leading location technology specialist renowned for its innovative mapping and navigation solutions used worldwide. Embarking on a role with Tomtom means stepping into a dynamic environment where technology and data drive advanced location-based services and products.

The Data Analyst position at Tomtom is pivotal, demanding a blend of strong analytical skills, data visualization expertise, and proficiency in handling large datasets. As a Data Analyst, you will support a variety of business areas, turning data into actionable insights to fuel strategic decision-making and enhance Tomtom’s product offerings.

With this guide by Interview Query, you will gain valuable insights into the interview process at Tomtom, including commonly asked questions and practical tips to help you succeed. Let's navigate this journey together!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining TomTom as a Data Analyst. Whether you were contacted by a TomTom 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 TomTom 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 TomTom 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 TomTom 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 TomTom’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 TomTom 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 TomTom.

Quick Tips For TomTom Data Analyst Interviews

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 TomTom interview include:

• Understand TomTom’s Products: TomTom questions often rely on situational scenarios with their products. Study TomTom’s range of products and understand how you would personally improve or utilize them.
• Be Data-Driven: TomTom’s data science interviews assess how well you can provide business-driving insights with data science. Ensure you have a solid understanding of statistics and probability, as these questions can be some of the hardest to solve.
• Embody the Culture: TomTom values innovation and collaboration. Be prepared to respond to behavioral questions with answers that touch on TomTom’s core values and demonstrate your ability to work effectively within their team environment.

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

• Write a query to get the average order value by gender. Given three tables representing customer transactions and customer attributes, write a query to get the average order value by gender. Round the answer to two decimal places.

• Write a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

• Find the index where the sum of the left half equals the right half in a list. Given a list of integers, find the index at which the sum of the left half of the list is equal to the right half. If no such index exists, return -1.

• Write a function sorting to sort a list of strings in ascending order. Given a list of strings, write a function sorting from scratch to sort the list in ascending alphabetical order. Do not use the built-in sorted function. Aim for (O(n \log n)) complexity.

• Write a query to extract the earliest date each user played their third unique song. Given a table of song_plays and a table of users, write a query to extract the earliest date each user played their third unique song. If a user has listened to less than three unique songs, display their name with a NULL date and song name.

• How would you build a model to predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, describe the steps and features you would use to build a predictive model for identifying potential merchants for acquisition when entering a new market.

• How would you determine the customer service quality through the chat box for small businesses on Facebook Marketplace? Your team at Facebook focuses on helping small businesses increase sales through the Marketplace app. Explain how you would assess the quality of customer service in chat interactions between small businesses and consumers.

• What business health metrics would you track on a dashboard for an e-commerce D2C sock business? As the person in charge of an e-commerce D2C business selling socks, list and explain the key business health metrics you would monitor on a company dashboard.

• Write a query to determine if user interactions (likes, comments) lead to higher purchasing volumes. Given three tables (users, transactions, and events), write a SQL query to analyze whether users who interact on the website (e.g., likes, comments) have a higher purchasing volume compared to those who do not interact.

• How does random forest generate the forest and why use it over logistic regression? Explain the process of generating a forest in a random forest algorithm and discuss the advantages of using random forest over logistic regression.

• How do we deal with missing square footage data to construct a housing price model? You have 100K sold listings over the past three years for Seattle, with 20% missing square footage data. Describe methods to handle the missing data to build an accurate housing price prediction model.

• How would you build a model to predict which merchants DoorDash should acquire in a new market? As a data scientist at DoorDash, outline the steps to create a model that predicts which merchants to target for acquisition when entering a new market.

• How do you detect and handle correlation between variables in linear regression? Describe methods to detect and manage correlation between variables in a linear regression model. Explain the consequences of ignoring such correlations.

• How would you design a model to detect potential bombs at a border crossing? Outline the design of a model to detect potential bombs at a border crossing, including the selection of inputs and outputs, accuracy measurement, and testing procedures.

• How many more samples are needed to decrease the margin of error from 3 to 0.3? Given a sample size (n) with a margin of error of 3, calculate the additional samples required to reduce the margin of error to 0.3.

• What is the mean and variance of the distribution of (2X - Y)? Given (X) and (Y) are independent random variables with normal distributions (X \sim \mathcal{N}(3, 4)) and (Y \sim \mathcal{N}(1, 4)), determine the mean and variance of (2X - Y).

• How do you calculate the sample size and power for an AB test?

• Explain how to calculate the sample size necessary for an accurate measurement in an AB test with both a test group and a control group.
• If the sample size is similar and sufficient between the two groups, should the power increase or decrease to measure very small differences?

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

Q: What is the interview process for the Data Analyst position at Tomtom?

A: The interview process at Tomtom typically involves multiple stages, including a phone screen with HR, a technical interview focusing on your analytical and technical skills, and an on-site interview where you may be given a case study or practical problem to solve. The process is designed to assess not only your technical abilities but also your fit within the company culture.

Q: What technical skills are required for a Data Analyst role at Tomtom?

A: For a Data Analyst position at Tomtom, you should have strong skills in SQL, data visualization tools like Tableau or PowerBI, and scripting languages such as Python or R. Proficiency in statistical analysis, data modeling, and experience with large datasets are also highly valued.

Q: What does the company culture at Tomtom look like?

A: Tomtom has a collaborative and innovative culture that emphasizes continuous learning and development. The company values transparency, teamwork, and a customer-centric approach. Employees are encouraged to take initiative and think creatively to solve complex problems.

Q: How can I stand out in a Tomtom interview for a Data Analyst position?

A: To stand out in an interview at Tomtom, demonstrate your problem-solving abilities, technical skills, and your understanding of the industry. Be prepared to discuss your previous projects in detail, showing not just the outcome, but also your thought process. Practicing with Interview Query can help you get accustomed to the type of questions you might face.

Q: What are some common challenges faced by a Data Analyst at Tomtom?

A: Common challenges include working with large and complex datasets, deriving actionable insights from data, and effectively communicating your findings to stakeholders. You may also need to work cross-functionally with different teams, requiring strong interpersonal skills and adaptability.

If you want more insights about the company, check out our main TomTom 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 TomTom’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 TomTom 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!