At TomTom, we're seeking a Data Scientist to join our Maps Quality and Product Insight team in Madrid.
As part of the team, you will help TomTom deliver the most up-to-date, accurate, and detailed maps and location services for the hundreds of millions of drivers and users of our maps and products around the world, enabling the future of autonomous driving.
The Maps Quality and Insight team is focused on providing state-of-the-art data & analytics solutions that enable fast and cost-effective data-driven strategic decision-making within TomTom and for our customers and partners.
The impact you'll make Drive strategic business decisions with insights obtained by manipulating large volumes of data from a variety of different sources: system logs, satellite imagery, vertical imagery, street-level imagery, GPS traces, etc., individually and by fusing several combinations of these sources.
Design, develop, and maintain data processing pipelines to use these data sources individually or combined and to predict various map features and attributes by applying statistical models, ML, and AI models.
State the quality level of our maps via statistical experiments that help us understand where we are and why, delivering effective insights that help drive our map editing strategy.
Develop processes and tools to monitor and analyze model and system performance and data accuracy.
Collaborate with teams from diverse backgrounds (e.g., data scientists, software engineers, product managers, map, and GIS experts) across the company and with our customers on projects and knowledge sharing.
What you'll need Minimum 3+ years of experience working as a Data Scientist or Software Engineer (with relevant experience in data analytics projects).
Bachelor's/Master's in Computer Science, Mathematics, Statistics, or equivalent field.
Good communication skills in English.
Strong problem-solving skills.
Team-oriented, able to communicate with team members, express doubts, and provide and accept constructive feedback.
Passion for programming with a solid foundation in software development, and eagerness to learn and improve skills.
Fair statistical knowledge and expertise in designing and testing experiments and drawing conclusions under uncertainty (sampling strategies, robust statistical estimation, etc.).
Experience in at least one object-oriented language – Python is a must; PySpark and Scala are a plus.
Experience in various ML/AI techniques and frameworks.
Knowledge of SQL and databases.
Experience in processing and analyzing data to draw insights and produce visualizations (data storytelling).
A passion for learning new technologies and techniques and a curiosity for exploring new possibilities and challenges.
What is nice to have Work experience in Big Data and cloud ecosystems (e.g., Spark, Databricks, Azure, AWS, GCP).
Prior experience working with geospatial and map data and/or with NoSQL databases.
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