ABOUT THE POSITION

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.

ABOUT YOU

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.

REQUIRED QUALIFICATIONS

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

Technical Skills
• 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

Approach and Mindset
• 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

QUALIFICATIONS CONSIDERED AS ASSETS
• Ph.D. or master's degree in electrochemical engineering, physics, applied mathematics, statistics, computer science, or a related quantitative field
• Specialized experience in BESS-specific analytics such as:
• Electrochemical model-based or data-driven SoH and RUL estimation
• Degradation and calendar/cycle life modeling
• Dispatch optimization and revenue stack modeling
• Augmentation strategy and capacity fade forecasting
• Thermal runaway risk modeling or fault detection
• Experience with real-time or near-real-time analytics pipelines
• Hands-on experience with data engineering concepts, cloud platforms (AWS, Azure, or GCP), and scalable data pipelines
• Knowledge of power markets, capacity markets, ancillary services, PPAs, or grid interconnection as they relate to BESS assets
• Experience with MLOps practices and large-scale model deployment
• Scientific publications, patents, or technical conference presentations in battery analytics, applied machine learning, or related fields

RESPONSIBILITIES

Advanced Analytics and Product Development
• Identify, evaluate, and prioritize high-impact advanced analytics opportunities focused on BESS performance, health, and revenue optimization
• Lead the development of advanced data science solutions from concept through production deployment
• Leverage Power Factors' large-scale operational BESS database to build analytically rigorous, scalable models used across global storage fleets
• Collaborate with product and engineering teams to ensure analytical solutions are robust, interpretable, and operationally actionable

Domain Expertise and Customer Engagement
• Apply deep BESS domain knowledge to define analytically sound problem formulations, feature engineering strategies, and model validation approaches
• Engage directly with technically sophisticated customers to explain analytical methods, assumptions, and results with clarity and precision
• Serve as an internal BESS subject matter expert, supporting product, sales, and customer success teams with domain guidance

Research and Innovation
• Stay current with advances in battery science, electrochemical modeling, grid storage economics, and ML for energy systems
• Propose and lead experiments to improve model quality, expand analytical coverage, and deliver new product capabilities
• Contribute to the external scientific and technical community through publications, conference presentations, or open-source contributions where appropriate