Data Scientist (BESS Performance Engineer)

Wizeline · Argentina · posted today ago

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About this role

BESS Performance Engineer

We are:

Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.

With the right people and the right ideas, there’s no limit to what we can achieve.

Are you a fit?

We are seeking a BESS Performance Engineer to join the Asset Management team, supporting a growing portfolio of distributed generation projects across the United States. Reporting to the VP of Engineering, this role will lead performance monitoring, analysis, and reporting for standalone Battery Energy Storage Systems (BESS) and solar-plus-storage assets, including AC- and DC-coupled configurations.

The ideal candidate combines expertise in battery performance modeling, renewable energy systems, and data analytics to optimize technical performance and commercial efficiency. Working closely with Data Science, Asset Management, Engineering, and Operations & Maintenance (O&M) teams, this individual will develop data-driven insights, automate reporting workflows, and identify opportunities to improve asset reliability, battery life, and energy market performance.

Key Responsibilities

BESS Performance Monitoring: Lead performance analysis, monitoring, and operational reporting for standalone BESS and paired solar PV + BESS assets across a distributed generation portfolio.
KPI Development & Tracking: Develop and monitor key performance indicators, including Round-Trip Efficiency (RTE), State of Health (SOH), State of Charge (SOC), auxiliary power consumption, and system availability.
Battery Degradation & Predictive Modeling: Develop degradation models and predictive analytics to forecast battery life, monitor SOH against capacity guarantees, and optimize charging and discharging cycles.
Data Analysis & Troubleshooting: Extract, clean, and analyze large-scale SCADA, DAS, telemetry, and discrete-event datasets to identify underperforming assets, diagnose component failures, and recommend corrective actions.
Data Integration & Automation: Collaborate with Data Science teams to integrate BESS telemetry into enterprise platforms, optimize data warehousing, and automate internal and external reporting pipelines.
Solar-Plus-Storage Performance: Evaluate the technical and operational impacts of transitioning from standalone BESS to AC- and DC-coupled PV + BESS configurations.
Performance Optimization & Reporting: Present technical and financial findings, recommend operational improvements and dispatch strategies, and communicate actionable insights to technical and non-technical stakeholders.

Must-have Skills

Bachelor's or Master's degree in Electrical Engineering, Computer Science, Data Science, Mathematics, Physics, or a related technical field.
3–5 years of experience in performance engineering, battery modeling, energy storage analytics, or a closely related field.
Strong understanding of Battery Energy Storage Systems (BESS), battery architecture, degradation mechanisms, and performance modeling.
Experience with the operation, design, or analysis of AC and DC electric power systems.
Proficiency in Python, R, or SQL for data analysis, time-series manipulation, and modeling.
Hands-on experience with SCADA, DAS, telemetry, and operational datasets for power plant performance assessment.
Experience with analytical and business intelligence tools, such as Pandas, NumPy, Matplotlib, Power BI, or Tableau.
Strong analytical and critical-thinking skills, with the ability to translate complex datasets into actionable insights.
Ability to work independently and collaborate effectively with cross-functional teams.
Proficiency in leveraging Generative AI tools and Large Language Models (LLMs) to accelerate code development, automate data processing, and improve analytical workflows.

Nice-to-have

Renewable Energy Experience: Direct experience evaluating the performance of distributed generation or utility-scale BESS and solar PV assets.
Energy Markets & Financial Optimization: Experience analyzing wholesale electricity markets, ISO/RTO dispatch strategies, Locational Marginal Pricing (LMP), energy arbitrage, and battery dispatch optimization.
Solar-Plus-Storage Expertise: Experience analyzing standalone battery storage and AC- or DC-coupled solar-plus-storage projects.
SCADA & Monitoring Platforms: Familiarity with platforms such as AlsoEnergy, GPM, Power Factors, Ignition, Wattch, Denowatts, SynaptiQ, or OSIsoft PI System.
Cloud & Data Infrastructure: Practical experience with cloud platforms such as AWS or Azure, data warehousing, and data pipeline development.
AI & Predictive Analytics: Experience designing and deploying AI-driven workflows, machine learning algorithms, and statistical models to improve predictive performance and operational efficiency.
Asset Management Systems: Familiarity with Computerized Maintenance Management Systems (CMMS), such as Fiix, IBM Maximo, or Sitetracker.
Experience collaborating with Asset Management, Engineering, Data Science, and O&M teams in renewable energy environments.