Lead Data Scientist

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HERE Technologies

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

🚀 Aerospace

🏢 Enterprise

Aerospace • Automotive • Enterprise

HERE Technologies is a leading provider of mapping and location data services, specializing in advanced location solutions for various industries, including automotive. Their products range from dynamic map content and routing services to tools for automated driving and fleet management. With a focus on precision and innovation, HERE Technologies empowers businesses with high-quality geographical data to enhance navigation and develop next-generation, software-defined vehicle systems.

📋 Description

• Own the evaluation framework and quality strategy for advanced AI and vision systems • Define pass/fail metrics for output quality, structural fidelity, temporal consistency, label quality, robustness, and operational repeatability • Own data and validation strategy for improving model quality and downstream usefulness • Lead artifact auditing, failure taxonomy development, release-quality reporting, and evidence-based prioritization • Measure whether outputs are suitable for perception, mapping, generative AI, and customer-facing use cases • Partner with model, simulation, and platform owners to drive quality improvements and production-readiness decisions • Build and evolve metric suites for output quality, fidelity, repeatability, and downstream usefulness • Define human-review protocols and product acceptance thresholds for complex AI systems • Evaluate whether outputs preserve the structure, semantics, and consistency expected by downstream applications • Translate evaluation findings into data strategy, experiment priorities, and applied modeling opportunities • Help define dataset design, validation slices, and quality-improvement loops across the product • Create experiment and release reports that turn technical output into clear product decisions • Help prioritize what the team should fix next based on evidence rather than intuition • Establish evaluation foundations that remain useful across future AI, perception, and mapping capabilities

🎯 Requirements

• Strong background in applied machine learning, computer vision, synthetic-data evaluation, or perception-system validation • Experience designing metrics and evaluation frameworks for generative, simulation, or perception systems • Experience connecting model behavior, data quality, and product outcomes in ambiguous AI systems • Ability to translate research-quality experiments into practical engineering and release decisions • Strong analytical judgment and clear written communication • Comfort owning both strategy and execution in a small team • Master’s or PhD in Computer Science, AI, Machine Learning, or related field • 5-8 years of experience in deep learning, computer vision, or multimodal AI.

🏖️ Benefits

• health (Medical/Dental/Vision) insurance • retirement savings plans • paid time off & leave policies