Sr. Data Scientist
This role focuses on leading advanced geospatial analytics and scalable GIS solutions, bridging technical expertise with business needs to deliver actionable insights. The Senior Data Scientist will mentor junior analysts, define technical standards, and architect enterprise-level spatial data products.
Skills required
About this role
Job Description:
The Senior Data Scientist – Geospatial serves as a technical leader responsible for designing and delivering advanced analytical and modeling solutions using geospatial data. This role leads complex spatial analytics efforts, mentors less‑experienced data scientists, and collaborates with GIS teams and business leaders to translate geospatial data into actionable insights. The position requires deep expertise in data science techniques and hands‑on experience with spatial analytics at scale
Responsibilities:
- This position leads the design and development of scalable GIS tools, analytical applications, spatial data products, and reusable geoprocessing capabilities that support complex business and operational needs.
- Responsibilities include establishing technical standards and development frameworks; guiding the architecture of enterprise geospatial solutions; developing and overseeing spatial data pipelines, APIs, and automation workflows; and integrating GIS capabilities with cloud platforms, enterprise data systems, and AI services.
- Candidates should hold an advanced degree, with at least 6-8 years of experience in data science and a preference for data science in GIS during the last 4 years.
- Extensive experience developing production-grade analytical tools and applications, and a strong track record of delivering enterprise-level business impact.
- Preferred qualifications include significant experience developing GIS tools and applications using Esri technologies such as ArcGIS Pro, ArcGIS Enterprise, ArcGIS Online, ArcPy, the ArcGIS API for Python, ArcGIS REST APIs, and ArcGIS Maps SDKs.
Experience developing custom geoprocessing tools, Python toolboxes, web-based mapping applications, dashboards, widgets, extensions, and automated spatial analysis workflows is highly valued.
