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Public energy-tech brand, popular data scientist title, metro Bangalore location, and mid-experience band increase applicant competition.
Strong preference for battery storage and energy-sector experience reduces cross-industry transferability.
Explicit 3–7+ years, mandatory Python/ML/production skills and energy-domain experience make filters strict.
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Develop and maintain advanced data science models including ML/AI and optimization for battery energy storage system (BESS) performance assessment, forecasting, anomaly detection, and predictive maintenance.
Create KPIs, alerts, visualizations, and reports to analyze and communicate BESS performance, degradation, and efficiency metrics to internal and external stakeholders.
Collaborate with cross-functional teams including product managers and software engineers to integrate analytics solutions into Fluence’s platforms and align on product requirements.
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 similar roles, preferably in energy sector or industrial automation.
Programming proficiency in Python or equivalent with experience in scientific libraries (NumPy, Pandas, Scikit-learn, TensorFlow, Pyomo, Plotly).
Experience developing production-grade scalable analytics solutions in collaboration with software engineering teams.
Experience specifically in energy sector domains such as battery storage, renewable energy, or power systems, with familiarity of battery performance, degradation, and storage technologies.
Demonstrated ability to independently manage technical projects from model development to deployment with minimal supervision and meet deadlines effectively.
Strong analytical skills with a track record of building actionable data-driven models and communicating complex results clearly to diverse stakeholders.