AI Energy Consumption Anomaly Detection Engineer

About the role

Responsibilities

• Engineer time-series features from equipment-level power monitoring: load cycles, demand spikes, baseline drift
• Train anomaly detection models distinguishing real equipment deviations from normal operational variation
• Develop equipment-specific baseline models handling seasonal load patterns and production schedule variation
• Build alert prioritization ranking anomalies by energy waste magnitude and failure probability correlation
• Create energy waste quantification estimating excess consumption cost for flagged anomalies
• Monitor alert precision tracking the rate at which flagged anomalies are confirmed as real issues by maintenance teams

Requirements

• 3+ years in industrial data science, time-series analytics, or IoT data engineering
• Strong Python, SQL, and scikit-learn skills with anomaly detection and time-series modeling
• Understanding of industrial equipment energy profiles, fault signatures, and predictive maintenance concepts
• Experience building alerting systems that balance sensitivity against alert fatigue
• Ability to work with facilities engineers on operational context and anomaly validation

Benefits

• Fully remote with flexible schedule
• Health and dental insurance
• $2,500 annual professional development budget
• 401(k) with match
• Performance bonus tied to client energy savings outcomes

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