Description

You will design and scale infrastructure to support data science workflows, focusing on labeling systems, visualization platforms, and data processing pipelines.

Responsibilities

• Build and scale tools for data labeling systems including Super Annotate, Labelbox, and Voxel51.
• Develop plugins for spatial visualizations over maps.
• Define, quantify, and analyze key performance indicators to monitor system performance.
• Scope work, estimate timelines, and execute deliverables within an Agile environment.
• Collaborate with engineers and data scientists to build, test, and communicate technical solutions to stakeholders.

Required Skills

• Production-ready Python development.
• AWS infrastructure management including S3 and policies.
• Data-access technologies: SQL, Spark, Databricks, and MongoDB.
• Management of diverse data types: images, rasters, parquet, time-series, geo-tagged, and unstructured text.
• Spatial visualization tools such as Folium and Plotly.
• Development of monitoring tools, including Tableau dashboards and automated email alerts.
• Statistical tool proficiency in SAS, SPSS, or SAS E Miner.
• Strong technical documentation and ability to communicate complex insights to non-technical audiences.
• Experience mining data for analytical insights.

Preferred Skills

• Plugin development using JavaScript.
• Knowledge of model validation, measuring model bias, and monitoring model drift.

Key Skills

Education

Any Graduate