Lead Data Scientist
- Discuss this with your agent
- Open in Claude
- Open in ChatGPT
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Role details
Tech stack
Job description
Advanced AI systems fail in ways that aggregate benchmarks often hide. HERE needs a technical leader who can determine whether models are accurate, robust, controllable and genuinely useful in downstream products.
You will lead evaluation and data strategy for AI, vision and perception systems. You will connect quantitative analysis, artifact review and real-world use cases to reveal failure modes, prioritize fixes and establish credible production-readiness standards.
Your work will shape what the team builds next, what data it needs and when a model is ready to move forward. What will you do?
- Define evaluation strategy, metrics, test sets and release gates for advanced AI, vision and perception capabilities.
- Build reproducible evaluation pipelines across model quality, robustness, controllability, coverage and downstream utility.
- Analyze model outputs and artifacts to identify failure patterns that summary metrics miss.
- Translate model behavior into prioritized recommendations for model, data and product teams.
- Design data-improvement loops, including dataset audits, gap analysis, sampling and targeted data acquisition or generation.
- Partner with scientists and engineers on experiment design, benchmarking and statistically sound comparisons.
- Communicate evidence clearly to technical leaders and product stakeholders, including tradeoffs and readiness decisions.
Requirements
You are a rigorous applied scientist who can move between statistics, model behavior, data quality and product impact.
- Strong experience evaluating machine-learning, computer-vision, multimodal or generative-AI systems.
- Advanced Python and SQL skills with experience building scalable analysis or evaluation workflows.
- Strong foundations in statistics, experimental design, error analysis and model validation.
- Experience converting ambiguous quality questions into measurable criteria and actionable decisions.
- Ability to inspect model outputs deeply, identify patterns and explain what should change next.
- Technical leadership skills and the ability to influence across data science, engineering and product.
It would be great if you also bring
- Experience with spatial, geospatial, sensor, map, trajectory or simulation data.
- Experience evaluating generative models, temporal consistency or perception systems.
- Familiarity with data-centric AI, active learning, synthetic data or human-evaluation programs.
- Graduate degree in a quantitative or technical discipline
Benefits & conditions
The expected base salary range for this position is $160,000 to $170,000 per year. Actual compensation will be based on factors such as skills and experience. This position is also eligible for an annual performance bonus, which is subject to company and individual performance.
Life at HERE comes with generous benefits to support your health and overall wellness. Benefits available to US-based HERE employees include health (Medical/Dental/Vision) insurance, retirement savings plans, paid time off & leave policies.
About the company
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.
Apply for this position
This job is hosted externally. Click below to view the full posting and apply.
Prepare application
- Draft this with your agent
- Open in Claude
- Open in ChatGPT
Good distractions
Talks and stories from around this role — technically off-topic, practically not.
Moments
Explore playlistsVideos
See allRelated articles
See all
Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud
How to start an AI project for a good cause and boost your career
Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production
Navigating the AI Shift