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Metro location and mid-level data science profile increase competition, but battery domain specialization narrows applicant pool.
Specialized battery storage and energy analytics expertise reduces cross-industry transferability.
Explicit 3+ years, mandatory battery/energy expertise, and production-grade Python/ML stack increase shortlisting strictness.
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Develop and maintain advanced analytics, KPIs, and alerts using operational battery data to assess performance, degradation, efficiency, and detect issues.
Build, train, and deploy first-principles, ML/AI, and optimization models for battery performance assessment and control applications including forecasting, anomaly detection, and predictive maintenance.
Create visualizations and reports to communicate model results and insights; collaborate with cross-functional teams to align on technical/product requirements and integrate models into platforms.
Bachelor’s degree in Data Science, Computer Science, Electrical/Mechanical/Chemical Engineering, Mathematics, or related field.
3 to 7+ years of professional experience in data science, software engineering, controls, operations research, or related roles, preferably in energy sector or industrial automation.
Proficient programming skills in Python or similar with experience in scientific libraries like NumPy, Pandas, Scikit-learn, TensorFlow, Pyomo, Plotly.
Experience building scalable, production-grade analytics solutions in collaboration with software engineering teams; solid understanding of energy sector with familiarity in battery storage and renewable energy technologies.
Experienced professional with a strong mix of data science, ML/AI, optimization, and battery energy storage knowledge to lead analytics projects delivering operational improvements.
Capable operator working effectively with cross-functional teams, product managers, and engineering to translate requirements into robust data solutions and implementations.
Has proven ability to produce maintainable, scalable production code and integrates analytics into operational platforms, demonstrating both technical depth and practical delivery focus.