Darum lohnt es sich
Key Responsibilities Design AI-ready data models to support machine learning, advanced analytics, and real-time decisioning Build and maintain feature-ready datasets for data science teams (feature engineering support) Develop semantic and analytical data layers for BI, AI, and self-service analytics Collaborate with data scientists to translate ML use cases into scalable data structures Model and integrate high-volume time-series and IoT data (e.g., smart meters, sensors, grid telemetry) Enable real-time / near-real-time data pipelines for AI-driven insights Ensure data models support MLOps frameworks (model training, validation, deployment pipelines) Implement data lineage, observability, and quality frameworks to support trusted AI outcomes Optimize data structures for lakehouse architectures Job Title: Data Modeling Expert – AI & Analytics
Location: California (Hybrid/Remote)
We are seeking a Data Modeling Expert with strong AI/Analytics focus to enable next-generation data platforms supporting predictive analytics, machine learning, and intelligent automation.
This role will design and optimize data models that power use cases such as grid reliability, predictive maintenance, wildfire risk modeling, customer analytics, and AI-driven operations .
