The ArcGIS platform is an expansive spatial data science platform, incorporating both specialized geospatial data science tools and cutting-edge open source components, helping our users develop workflows that power modern business and make the world a better place for future generations. Be part of the team that deepens this integration by expanding the scope of geospatial data exploration and data analysis pipelines empowering users to tackle complex problems and communicate those results.
Data science continues to evolve, and this senior role is intended for an engineer with existing data science experience who wants to make an impact by bridging the gap between research activity and a platform enabling a broad base of users to perform data science. This includes incorporating innovations in columnar databases and efficient analytic operations crossing the CPU / GPU boundary, understanding modern data science workflows in a spatial context, and integrating knowledge across scientific and software engineering domains. These efforts will provide building blocks of a system which meshes organizations' existing data science workflows with the depth and power of the ArcGIS platform system of record.
Responsibilities
- Spearhead the expansion of our python data science experience within ArcGIS
- Design the integration of geospatial data exploration and data analysis pipelines with innovations in the broader data science ecosystem (such as the Arrow columnar database or GPU based analysis)
- Represent a broad range of data science users who work at the intersection of spatial analysis and broader data science workflows
- Help spatial data science workflows mesh well with other data science workflows to streamline our users' work and the reach of our existing tools and technology
- Work with multiple teams to design, implement and deploy the technologies within the ArcGIS products
Requirements
- 5+ years of practical experience solving problems using a broad range of data science tools
- Extensive experience with data frames, such as Pandas, Geopandas, R, or polars
- Experience with Notebooks and their use in data science
- Experience with practical data science languages such as Python, R, or Julia
- Experience performing data extraction, transformation, and loading from multiple sources
- Strong communication skills, including conveying complex topics to non-technical audiences
- Bachelor's in computer science, geography, statistics, mathematics, physics or a similar field
Recommended Qualifications
- Experience interacting with AWS, Azure, or other cloud service
- Experience producing data visualizations using tools such as matplotlib, seaborn, or bokeh
- Experience handling massive batch/streaming data using big data tools, such as Apache Spark
- Experience working with modern data workflows, such as Streamlit or DuckDB
- Experience building and optimizing supervised and unsupervised machine learning models including deep learning and various other modern data science techniques
- Experience with lower-level development stacks such as C++, Rust, or CUDA
- A fundamental understanding of mathematical and machine learning concepts such as calculus, back propagation, ReLU, Bayes’ theorem, Random Forests, time series analysis, and more
- Experience with software development best practices (version control)
- Experience with applied statistics concepts
- Experience with spatial and GIS concepts
- Master’s in computer science, geography, statistics, mathematics, physics or a similar field