RAVE I, Data Enrichment

About the role

The role centers on improving map data quality for navigation and location services. You support cartographic accuracy for people, packages, and vehicles. The work targets organizations that rely on flexible and privacy compliant location platforms.

Data roles turn raw information into decisions. Analysts query databases and build dashboards. Data scientists build models that predict outcomes. Data engineers build the pipelines that move and store data. All three work closely with business teams and need a mix of statistics, coding, and communication. Nearly every modern company runs on data teams, from startups to banks. A strong portfolio of past analyses matters more than degrees in many hiring decisions.

Key facts

What you'll do

Objects in images are detected and marked to meet defined requirements. Large volumes of data, reaching several tens of thousands of images or map features weekly, are analyzed, classified, and sorted. Data validation and editing support the creation of map and navigation service content.

Requirements

A degree is required as stated in the source materials. The ability to execute monotonous work at high volume while maintaining personal efficiency is necessary. Focus on repetitive tasks must be sustained to ensure high quality and accuracy in data processing. Logic, independent reasoning, and action are required traits. Resilience in rapidly changing situations is expected. Quick learning and adaptation between projects with different workflows or instructions are essential. Teamwork and high communicative skills are mandatory. Clear written and verbal English at A2+ level is required, with the proficiency level noted in the CV. Office attendance is required for the first three months during probation, with periodic presence for team sprints.

Nice to have

General knowledge of traffic rules supports quality analysis of traffic situations and driver behavior modeling. Understanding OpenStreetMap service and interest in cartography are welcomed, including OSM edit history. Experience in GIS, cartography, or geodesy is advantageous. Experience in the IT sector or completed IT courses help understand communication culture in a high-technology international company.

Practical notes

This role operates under the privacy notice for applicants provided by Mapbox. Personal data submission is mandatory for application processing. Employment is subject to non discrimination commitments for all protected classes. Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.

Good to know

Work in this field involves processing spatial data to improve digital maps. Common tools include mapping editors and data validation platforms. The role emphasizes accuracy and consistency when handling large datasets. Continuous learning supports adaptation to updated procedures and standards. Collaboration with distributed teams is a standard part of the workflow.

Questions to ask

Worth asking in any interview: how the team measures success, who the role works with daily, what the onboarding looks like, and what the company is trying to achieve this year. Asking what past hires did well is a strong final question. Keep the list short and pick the questions that matter most to you.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.