Gridware

Data Scientist, Forecasting

Gridware

full-time

Posted on:

Location Type: Hybrid

Location: San FranciscoCaliforniaUnited States

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Salary

💰 $180,000 - $200,000 per year

Tech Stack

About the role

  • 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.

Requirements

  • 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
Benefits
  • Health, Dental & Vision (Gold and Platinum with some providers plans fully covered)
  • Paid parental leave
  • Alternating day off (every other Monday)
  • “Off the Grid”, a two week per year paid break for all employees.
  • Commuter allowance
  • Company-paid training
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
forecasting modelsPythonSQLdata ingestionfeature engineeringmodel validationmodel deploymentmodel monitoringdrift detectionretraining strategies
Soft Skills
cross-functional collaborationcommunicationanalytical thinkingproblem-solvingactionable recommendations