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Senior Data Analyst, Fleet Triage & Operations

External
gridware logoGridware · San Francisco, CA
Full-timeHybrid1mo ago
Data Analysis
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Benefits

Health, Dental & Vision (Gold and Platinum with some providers plans fully covered)Paid parental leaveAlternating day off (every other Monday)"Off the Grid", a two week per year paid break for all employees.Commuter allowanceCompany-paid training

Additional Information

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 Overview The Data Analyst, Fleet Triage & Operations owns the front line of fleet issue detection, prioritization, and incident learning at the device health layer - sitting at the interface of Gridware's hardware programs, including Gridscope and our connectivity solutions. As the deployed fleet scales, telemetry volume grows faster than any team can manually inspect, and not all signals matter equally. This role separates signal from noise, ensures the right issues reach the right teams before they become incidents, and leads the postmortem process to make sure the same class of issue doesn't go undetected twice. You'll design and operate a tiered triage pipeline, tune the detection logic that surfaces emerging device health issues, and facilitate postmortems end-to-end - from incident timeline reconstruction through action item closure. This is a highly cross-functional role that blends data analysis, operational rigor, and structured incident learning across hardware, firmware, and connectivity domains. This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!


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