Impress employers and recruiters.
Choose from hundreds of resume examples.

Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

Lead the design and development of scientifically rigorous analytics solutions leveraging extensive operational data, focusing on Battery Energy Storage Systems (BESS). This role involves hands-on work with Python and modern AI frameworks to develop production-grade analytical models addressing complex BESS problems, directly informing core platform capabilities.

Responsibilities

• 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.
• 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.
• 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.

Requirements

• 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.
• 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.

Skills

• Python
• pandas
• NumPy
• scikit-learn
• TensorFlow
• PyTorch
• Statistics
• Machine Learning
• Applied AI
• Time-series analysis
• Signal processing
• Anomaly detection
• Forecasting
• Predictive modeling
• Git
• Collaborative software development
• BESS domain expertise
• Battery electrochemistry
• BMS data
• System-level operations
• Performance drivers
• Degradation mechanisms
• Grid service delivery
• Data engineering
• Cloud platforms (AWS, Azure, or GCP)
• Scalable data pipelines
• Power markets
• Capacity markets
• Ancillary services
• PPAs
• Grid interconnection
• MLOps
• Large-scale model deployment

Location

• Remote

Work Type

• Full-time

Experience Level

• Senior-level
• 5+ years of experience in the energy industry

Education Level

• Ph.D. or master's degree in electrochemical engineering, physics, applied mathematics, statistics, computer science, or a related quantitative field

About the Company

• 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.

Equal Opportunity

• Power Factors is an Equal Opportunity Employer committed to engaging a diverse workforce and sustaining an inclusive culture.
• All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.