HERE Technologies
Principal / Lead Data Scientist (Python, ML, and Big Data)- m/w/d
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We are seeking a Principal / Lead Data Scientist to join our team focused on redefining the next generation of navigation and map interface technologies at HERE. In this role, you will apply scalable machine learning and Big Data techniques to enable global-scale digital map-making, directly impacting the quality and intelligence of HERE’s geospatial offerings. You will lead innovation in applied data science, collaborating with cross-functional teams to develop and deploy features that power intelligent mapping, navigation, and automotive-grade location solutions.
Key Responsibilities
Design and implement machine learning solutions for next-generation navigation and mapping products.
- Apply statistical modeling and data science best practices to real-world mapping challenges.
Collaborate across product, engineering, and design teams to deliver scalable, user-facing features.
- Employ a highly scalable Big Data infrastructure and machine learning as applied to global-scale digital map-making.
- Bring to bear the state-of-the-art in data science within new product offerings to address emerging challenges in the industry
- Collaborate with cross-functional teams to define, design, and ship new features. Conduct code reviews to ensure code quality and adherence to coding standards
Tech Stack :Python, Spark, Hadoop, Docker, AWS, Gitlab, UV, C ,Poetry, and GeoPandas
Note: this is an individual contributor role
Who are you?- Bachelor or Master’s degree in Computer Science/ IT /Information Systems or equivalent.
- 10+ years of experience in applied data science and ML, with a track record of product-driven outcomes.
Strong Python programming skills, including experience in data processing, model development, and deployment.
Deep understanding of machine learning, probability, and statistical methods.
Experience with distributed computing frameworks such as Spark or Hadoop.
Hands-on experience in cloud environments (e.g., AWS) and containerized workflows.
Nice-to-Have Skills
Mapping or automotive industry experience
Deep learning and/or computer vision expertise
C programming knowledge
Familiarity with Docker, Poetry, uv, or similar build tools
Experience with geospatial libraries (e.g., GeoPandas)
Understanding of map projections, coordinate systems, and 3D geometry
What Do We Offer?
- A great work-life balance
- 30 paid vacation days
- Hybrid model of work (2 days office and 3 days home office per week)
On-site Gym and Sauna – Stay active and unwind with our fully equipped fitness center and relaxing sauna.
Yoga Room – A dedicated space for mindfulness, stretching, and relaxation.
- Work on the development of high-scale services, serving and storing petabytes of data
- Work with cutting-edge, modern technologies
- Flexible working hours
- Competitive salary plus bonus
- BVG Ticket (For Berlin location)
- German language course (For Germany-based employees)
- Employee wellness programs and life-coaching sessions
- A diverse team of fantastic & talented people from 60+ countries worldwide.
- Brown bag talks, team events, BBQ on the rooftop, and more!
Change is HERE. Apply Now!
As part of HERE Technologies employment process, candidates will be required to successfully complete a pre-employment screening process. This offer and any related claims are subject to the successful completion of a pre-employment screening. This will involve employment, education, and criminal verification if applicable.
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Who are we?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 on our YouTube Channel.
