Industry Experience and BESS Expertise
• 5+ years of experience in the energy industry, with a strong emphasis on utility-scale battery energy storage systems
• Deep, hands-on understanding of BESS operation, performance, state-of-charge and state-of-health estimation, thermal management, degradation mechanisms, and lifecycle management
• Demonstrated experience working with large-scale operational BESS datasets, including BMS telemetry, SCADA, event logs, cycle data, and high-frequency time series
• Proven experience developing analytical solutions used by asset owners, operators, integrators, or OEM-adjacent organizations to support operational and strategic decision-making
• Proficiency in Python and modern data science libraries (pandas, NumPy, scikit-learn, TensorFlow / PyTorch, etc.)
• Strong grounding in statistics, machine learning, and applied AI, with demonstrated real-world deployment experience
• Experience with time-series analysis, signal processing, anomaly detection, forecasting, and predictive modeling in industrial or electrochemical contexts
• Experience with version control (Git) and collaborative software development practices
Collaboration and Communication
• Ability to clearly communicate complex analytical concepts, assumptions, and results to both technical and non-technical stakeholders
• Experience working closely with software engineering teams in production environments (APIs, services, deployment pipelines)
• Proven ability to translate operational challenges and customer needs into analytically sound and implementable solutions
• High degree of autonomy and ownership in complex, technically ambiguous problem spaces
• Strong scientific rigor, intellectual curiosity, and attention to detail
• Comfort working on long-horizon, technically demanding problems where analytical quality and robustness are critical