• Develop and evaluate machine learning models to support automation and quality improvement.
• Perform data exploration, feature engineering and model training using large geospatial and real-world datasets.
• Support development of ML pipelines and algorithms for map feature inference and attribute prediction.
• Analyze data and model outputs to identify insights, patterns and opportunities for improving accuracy.
• Collaborate with engineers and data scientists to implement and test models within production systems.
• Contribute to experimentation, model evaluation and documentation within the project team.

You are determined and have the following to be successful in the role:

• Degree (MS preferred) in Statistics, Applied Mathematics, Computer Science, Data Science, or related field.
• 2+ years of experience in Data Science, Machine Learning, or Applied Analytics.
• Strong understanding of machine learning fundamentals and statistical modeling.
• Experience using Python and common ML libraries.
• Ability to work with large datasets and perform data analysis and visualization.
• Strong problem-solving and analytical thinking skills.

Preferred Skills

• Exposure to deep learning models or computer vision techniques.
• Experience working with geospatial datasets or location-based data.
• Familiarity with data pipelines, ML experimentation frameworks, or model evaluation techniques.
• Basic understanding of model deployment and production ML systems.
• Experience working in collaborative, cross-functional teams.

HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes – from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely.

At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people’s lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us. Watch Video