Senior Data Scientist, Forecasting

United States·San FranciscoFull-Timemid

Data ScienceData ScientistDataData & AI

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Quick Summary

Overview

About Gridware Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of…

Technical Tools

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About Gridware

Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io.

Role Description:

As a Senior Data Scientist, you will be directly embedded into Gridware’s operations and analytics team and play a critical role in helping forecast weather based events, staffing of analysts, and gain a deeper understanding of how dynamic Gridware’s operations center can be.

Build and productionize forecasting models to predict weather-driven grid events, hazard incidence, and downstream operational workload.

Develop demand forecasts for analyst staffing, incorporating weather signals, seasonality, geographic deployment footprint, and historical event patterns.

Quantify relationships between environmental factors (e.g., wind, precipitation, temperature, vegetation conditions) and hazard/event types across service territories.

Design end-to-end modeling pipelines, including data ingestion, feature engineering, model validation, deployment, and monitoring.

Establish model performance tracking, drift detection, and retraining strategies to ensure reliability in dynamic conditions.

Translate model outputs and uncertainty into clear, actionable recommendations for operational leadership.

5+ years of experience building and deploying models into production environments

Experience with forecasting models

Strong programming skills with demonstrated proficiency in Python and SQL

Experience working within modern software stacks, including cloud platforms, containerization, and CI/CD workflows

Experience working cross-functionally with operations or business stakeholders

Experience working with weather data

Experience with Geospatial tooling (GIS tools, GeoPandas, etc.)