Senior Data Scientist, Fleet Performance Optimization

About GridwareGridware 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 DescriptionAs a Senior Data Scientist, you will be embedded within Gridware’s Fleet team, driving fleet performance optimization across our network of IoT devices.You will work across hardware, firmware, connectivity, and backend systems to understand real-world system behavior and optimize performance end-to-end. A core focus of this role is balancing competing system constraints—such as power consumption, data fidelity, connectivity reliability, and anomaly detection latency—to ensure optimal fleet performance.This role combines modeling, experimentation, and hands-on investigation to ensure reliable, scalable system performance in dynamic, real-world environments.Responsibilities Develop models and analyses to optimize system performance across competing constraints (e.g., power usage vs data quality vs responsiveness)Define and implement end-to-end observability, establishing metrics across system components and dependenciesDesign and run experiments (e.g., pre/post, control vs test) to evaluate changes and detect regressions at both component and system levelsBuild and refine anomaly detection and failure analysis methods across complex, real-world dataLead ad hoc investigations into system issues, identifying root causes and driving resolution with cross-functional teamsTranslate insights into actionable recommendations across Firmware, Hardware, Software, and Operations, driving measurable improvements in system behaviorDevelop predictive systems for early issue detection and performance forecasting, including in environments with limited historical dataContinuously evolve analyses into scalable intelligence systems that support monitoring, decision-making, and automationRequired Skills5+ years of experience in data science working on production systems or real-world applicationsProven experience building, deploying, and maintaining models in production environmentsStrong proficiency in Python and SQLExperience working with complex, real-world datasets (e.g., time-series, event-based, or system-generated data)Strong foundation in statistical analysis, experimentation, and/or anomaly detectionProven ability to bring structure to ambiguous, open-ended problems, iterating quickly to drive toward practical, high-impact solutions (80/20 mindset)Experience working cross-functionally with engineering and operational teamsBonus SkillsExperience working on distributed hardware/software systems such as robotics, autonomous vehicles, IoT fleets, charging infrastructure, or energy/grid systemsPrior ownership of end-to-end performance, reliability, or optimization for large-scale, real-world systems operating in dynamic environmentsThis 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!BenefitsHealth, 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