Demonstrated competency in developing production-ready code using Python & AWS infrastructure (e.g. S3, policies, etc).
Proficiency in using data-access technologies such as SQL, Spark, Databricks, MongoDB.
Experience with data storage and management of various types of data (e.g. images, rasters, parquet, time-series, geo-tagged, text, and other unstructured data).
Familiarity with spatial visualization tools (e.g. Folium, Plotly), and labeling systems like SuperAnnotate, Labelbox, Voxel51.
Experience in developing alerts (e.g. through email automation), dashboards (e.g. Tableau), or other means to monitor system performance and issues.
Excellent communication skills, including the ability to lead meetings, document work for reproduction, write persuasively, communicate proof-of-concepts, and effectively take notes.
Capacity to communicate complex analytical insights in a manner understandable by non-technical audiences.
Experience developing plugins with other programming languages such JavaScript.
Knowledge of model validation, measuring model bias, and measuring model drift.
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