Renewable Energy Performance & Data Analytics Specialist

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? Sounds awesome, right? Now, let’s make sure you’re a good fit for the role:

Key Responsibilities

• Analyze operational and time-series data from solar photovoltaic (PV) plants and Battery Energy Storage Systems (BESS) to evaluate performance, identify trends, and optimize asset operations.

• Collaborate with performance engineers and Operations & Maintenance (O&M) teams to investigate underperformance, identify root causes, detect potential equipment failures, and recommend corrective actions.

• Perform solar PV performance modeling and loss analysis, evaluating metrics such as Performance Ratio (PR), energy production, availability, clipping, soiling, inverter performance, tracker behavior, and temperature derating.

• Analyze BESS performance using metrics such as round-trip efficiency (RTE), state of health (SOH), state of charge (SOC), degradation, capacity fade, cycle aging, calendar aging, and auxiliary consumption.

• Develop predictive models, statistical analyses, and operational forecasts to support performance optimization and ensure assets meet energy production and capacity targets.

• Integrate telemetry and operational data from Data Acquisition Systems (DAS), SCADA platforms, inverters, weather stations, battery management systems (BMS), energy management systems (EMS), and power conversion systems (PCS).

• Develop and maintain data pipelines, ETL/ELT processes, and API integrations to consolidate operational data with weather sources and enterprise systems, including CMMS, ERP, and other asset management platforms.

• Automate performance reporting, data quality checks, analytical workflows, and operational processes using Python, R , SQL, and cloud-based technologies.

• Collaborate with engineering, O&M, Software/IT, and Asset Management stakeholders to translate technical findings into actionable recommendations that improve asset reliability, energy production, and operational cost efficiency.

• Present analytical results, performance trends, root cause analyses, and optimization recommendations to technical and non-technical stakeholders.

• Leverage AI-driven workflows to accelerate analytical development, automate repetitive tasks, and improve operational decision-making.

Must-have Skills

• Master's degree in Data Science, Computer Science, Mathematics, Physics, Electrical Engineering, or a related technical field.

• At least 5 years of combined experience in renewable energy performance engineering and data science, analytics, or a closely related role .

• Hands-on experience in the renewable energy sector, particularly with solar PV performance analysis, modeling, or asset performance optimization.

• Experience with solar PV performance modeling tools such as PVsyst, pvlib, or NREL SAM .

• Strong proficiency in Python and SQL for data processing, time-series analysis, modeling, and automation.

• Experience analyzing operational data from solar PV assets and identifying underperformance, energy losses, equipment issues, and root causes.

• Knowledge of performance metrics and operational concepts, including Performance Ratio (PR), availability, inverter performance, clipping, soiling, temperature derating, and loss analysis.

• Experience working with SCADA, DAS, telemetry, or other industrial operational data systems .

• Practical experience with time-series data across the data lifecycle, including data collection, cleaning, validation, analysis, modeling, and communication of results.

• Experience developing and maintaining ETL/ELT pipelines, integrating APIs, and working with structured datasets.

• Experience with predictive analytics, statistical methods, feature engineering, and data-driven performance forecasting.

• Strong analytical and problem-solving skills, with the ability to communicate complex technical findings and collaborate across engineering, operations, and business teams.

Nice-to-have:

• AI Tooling Proficiency : Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows.

• Experience with BESS performance analysis , including RTE, SOH, SOC, degradation, capacity fade, cycle aging, calendar aging, and auxiliary consumption.

• Familiarity with BESS architectures and components, including BMS, EMS, PCS, and AC-coupled or DC-coupled systems.

• Experience evaluating PV plant performance testing against relevant IEC and ASTM standards .

• Knowledge of weather data sources and services, including NOAA and satellite-based weather providers.

• Experience with SCADA, DAS, and asset performance monitoring platforms such as AlsoEnergy, Power Factors, Ignition, Wattch, Denowatts, SynaptiQ, or PI System.

• Experience with CMMS platforms such as Fiix, Maximo, Sitetracker, or Softwrench.

• Experience with cloud platforms such as AWS or Azure and business intelligence tools such as Power BI, Tableau, or Hex.

• Advanced Microsoft Excel skills, including VBA and macros.

• Experience using Generative AI tools and LLMs to accelerate code development, automate data processing, and streamline analytical workflows.

• At least 2 years of experience leading data science or performance analytics projects involving cross-functional collaboration.

• PMP or another recognized project management certification.

What we offer:

• A High-Impact Environment

• Commitment to Professional Development

• Flexible and Collaborative Culture

• Global Opportunities

• Vibrant Community

• Total Rewards

*Specific benefits are determined by the employment type and location. Find out more about our culture here