Senior Data Scientist - BESS

ABOUT POWER FACTORS

Power Factors is a leading software and solutions provider supporting the next generation of clean energy through Unity, one of the most comprehensive and widely deployed Renewable Energy Management Suites (REMS) in the market. The company manages more than 300 GW of wind, solar, and energy storage assets globally, serving over 600 customers and 18,000 sites.

Power Factors' Unity REMS suite spans the full energy value chain — from supervision and control through advanced analytics and market analysis. Through open, data‑driven applications, the platform enables renewable energy organizations to automate critical processes, integrate complex operational data, and make high‑confidence decisions to optimize asset performance and lifecycle value.

Drawing on deep domain expertise, Power Factors deploys advanced analytics and AI at scale to enable asset owners and operators to improve reliability, availability, and long‑term value as the global energy system transitions to clean energy.

Power Factors fights climate change with code.

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As a Senior Data Scientist – BESS, you will lead the design and development of scientifically rigorous analytics solutions leveraging Power Factors' extensive operational data, covering more than 300 GW of renewable energy assets — including one of the world's largest battery energy storage datasets.

This role is centered on deep BESS domain expertise, advanced statistical and machine learning methods, and large‑scale operational data. You will work hands‑on in Python and modern AI frameworks to develop production‑grade analytical models that address complex problems in battery performance, state‑of‑health estimation, degradation forecasting, dispatch optimization, and asset lifecycle management.

You will collaborate closely with software development teams, product management, and technically sophisticated customers to translate real‑world operational challenges into robust analytical solutions integrated into Power Factors' core platform. Your work will directly inform product capabilities used by leading BESS asset owners and operators globally.

This position offers the opportunity to apply advanced analytics at unprecedented scale to materially improve the performance and economics of battery energy storage assets worldwide.

You are a senior‑level data scientist and recognized BESS subject‑matter expert with substantial experience working with utility‑scale battery energy storage systems. You possess deep understanding of battery electrochemistry, BMS data, system‑level operations, performance drivers, degradation mechanisms, and grid service delivery — and you have applied advanced analytics to these challenges in real operational environments.

You are highly proficient in Python, statistical modeling, machine learning, and AI, with a track record of interpretable, physics‑informed, and operationally robust approaches. You are comfortable working with real‑world high‑frequency industrial time series and understand how analytical assumptions translate into operational and commercial decisions.

You work effectively with software engineers and are comfortable contributing to production‑quality code, reviewing model implementations, and discussing tradeoffs related to scalability, latency, and maintainability.

You are motivated by solving hard, real‑world problems in energy storage using advanced analytics and by seeing your work deployed at scale across large, diverse BESS fleets.

• 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…