Design and deploy ML and data-driven solutions to detect, validate, and reduce map quality issues (e.g. data drift, feature distribution shifts across countries, road classes, and sources).
Define and drive data analysis and model evaluation standards, including advanced and segmented performance metrics.
Lead the productionization of models and data pipelines, working closely with engineers and data engineers, including pipeline optimization.
Build and improve end-to-end automated workflows (from issue detection to resolution and closure), minimizing manual processes.
Perform code reviews and optimization, ensuring high-quality, production-ready solutions.
Mentor and guide less experienced scientists; contribute to planning and coordination of data science initiatives.
Requirements
4+ years of experience in data science / applied science roles (Senior level).
Strong expertise in machine learning (supervised, unsupervised, and dimensionality reduction techniques) and model selection.
Excellent Python skills and experience with large-scale data processing (e.g. Spark, big data environments).
Proven experience in building and deploying data pipelines and ML solutions in production.
Strong communication skills and ability to explain complex concepts to both technical and non-technical stakeholders.