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# Lead Data Scientist

- **Company:** HERE
- **Location:** Burlington, MA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $160,000.0 - $170,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Python (Programming Language), Machine Learning, Standard Sql, Model Validation, Generative AI, Data Strategy
- **Published:** August 31, 2026
- **Apply:** https://www.disabledperson.com/jobs/74699567-lead-data-scientist

## About the Role

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

## 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.


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