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Metro location and popular Data Scientist title balanced by niche geospatial and deployment requirements.
Core ML skills are transferable, but geospatial and public-sector program experience increases domain specificity.
Requires specific ML frameworks, geospatial experience, and independent project ownership, but no explicit years filter.
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Lead or contribute to AI and machine learning projects from framing through deployment, building data pipelines and models that support PxD's programs.
Identify and apply AI/ML solutions for program delivery, targeting, and impact measurement improvements.
Collaborate closely with technical teams and program leads, support quality assurance and maintain documentation and technical resources.
Degree in quantitative field (computer science, statistics, economics, engineering) or equivalent experience.
Proficiency in Python and/or R with experience in at least one ML framework (scikit-learn, PyTorch, TensorFlow).
Experience independently leading data science or AI projects across multiple stages (framing to deployment).
Experience with geospatial or remote sensing data (satellite imagery, GIS tools like QGIS or ArcGIS).
Capable of working independently on end-to-end data science or AI projects; senior level required to lead projects and mentor juniors.
Experienced in handling complex, real-world datasets rather than only academic or clean data sets.
Comfortable collaborating with government or public-sector stakeholders and working in cross-functional, multi-team contexts.