Prepare for and practice interview questions from Tomtom.

Tomtom Interview Questions

A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

Tomtom Interview Guides

<ul>
<li>At TomTom, we revolutionize the way people navigate the world. From introducing the first portable navigation device in 2004 to engineering the world's smartest real-time map today, our innovations shape how the world moves. With a global team of 3,700 unique, curious, and passionate problem-solvers, we open up endless possibilities for car manufacturers, enterprises, and developers.</li>
</ul>
In this guide, we'll delve into TomTom’s interview process and common questions you might face at each stage. Discover what it takes to join a company that values diversity, fosters personal growth, and offers the flexibility to work from anywhere. At TomTom, you'll find a place where your creativity meets world-changing technology—making a real impact every day. Dive in to prepare for your journey with us!

- At TomTom, we revolutionize the way people navigate the world. From introducing the first portable navigation device in 2004 to engineering the world's smartest real-time map today, our innovations shape how the world moves. With a global team of 3,700 unique, curious, and passionate problem-solvers, we open up endless possibilities for car manufacturers, enterprises, and developers.

In this guide, we'll delve into TomTom’s interview process and common questions you might face at each stage. Discover what it takes to join a company that values diversity, fosters personal growth, and offers the flexibility to work from anywhere. At TomTom, you'll find a place where your creativity meets world-changing technology—making a real impact every day. Dive in to prepare for your journey with us!

Overview

Suppose there exists a new airline named Jetco that flies domestically across North America. Jetco recently had a study commissioned that tested the boarding time of every airline, and it came out that Jetco had the fastest average boarding times of any airline.

What factors could have biased this result, and what would you look into?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

Boarding Times Bias

A new airline came out as the fastest average boarding times compared to other airlines.  What factors could have biased this result and what would you look into?

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

In an A/B test, how can you check if assignment to the various buckets was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

In an A/B test, which of the following is a common method to determine if the assignment to the test groups was truly random?

Random Bucketing

A/B Testing & Experimentation

Tomtom Salaries by Position

We’re looking for a Product Manager to own the strategy, roadmap, and adoption of internal data and analytics capabilities used by product teams. You’ll work closely with engineering, data science, and business stakeholders to translate real product needs into scalable platforms and best practices. What You'll Do <ul><li>Own the vision, strategy, and roadmap for data & analytics capabilities that enable product teams to be truly data-driven and product-led</li><li>Lead the end-to-end product lifecycle—from discovery and scoping through development, rollout, and continuous improvement</li><li>Drive cross-team alignment and stakeholder buy-in across engineering, data science, and business teams</li><li>Advance trusted metrics and governance shape frameworks for metric definitions, quality, monitoring, and alerting</li><li>Evolve our data architecture—helping move toward data mesh-inspired models (decentralized ownership, federated governance) while balancing centralized needs</li><li>Contribute to key technical decisions—you’re fluent discussing data storage, APIs, event schemas, and analytics/ML needs with engineers and data scientists</li><li>Champion operational excellence—embed data quality practices, efficient pipelines, access controls, and compliance guardrails into daily work</li><li>Evangelize and educate help build a data-driven culture through playbooks, enablement, and training </li></ul>What You'll Need <ul><li>8+ years in Product Management (or similar roles building data platforms/products), delivering outcomes with cross-functional teams</li><li>Technical depth comfortable with data architectures and analytics workloads; able to discuss schemas, telemetry, storage options (warehouses/lakes), APIs, and experimentation frameworks</li><li>Experience with data mesh or similar decentralized data ownership/governance models, or migrating from silos to hybrid approaches</li><li>Proven ability to set vision/OKRs, make clear product decisions amid ambiguity, and align multiple stakeholder groups</li><li>Track record improving metrics quality and trustworthiness (definitions, monitoring, anomaly detection, freshness/latency) and enabling self-service analytics at scale</li><li>Exposure to AI/ML enablement for product teams (agent-assisted analytics, analytics stores optimized for LLMs, vector search, etc.)</li><li>Experience shaping data governance & access control across multiple systems with varying sensitivity levels </li></ul>We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Question	Topic	Difficulty	Ask Chance
Boarding Times Bias	Statistics	Medium	Very High
Hundreds of Hypotheses	Statistics	Medium	Very High
Random Bucketing	A/B Testing & Experimentation	Medium	Very High

Tomtom Interview Questions

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Tomtom Interview Questions

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