Data Scientist - 21005

Role: Data Scientist
Priority Location: Latin America, India, Pakistan
Working Hours: Monday-Friday, 8:00am- 5:00pm EST
Target Start Date: ASAP (Urgent Hiring)

The final offer is at the client’s discretion and will depend on the candidate’s interview result, skills, and experience.

About the Company:

A certified B-Corp that develops, owns, and operates community-scale solar and energy storage projects, specializing in transforming underutilized land—such as brownfields and landfills—into clean energy assets. By combining renewable power generation with sustainable dual-use land solutions like pollinator-friendly ground cover and solar grazing, the company focuses on revitalizing local communities while advancing environmental restoration.

About the Role:

This position will work within the Asset Management team, which is responsible for the management of a growing portfolio of distributed generation projects located across the United States. This position reports to VP, Asset Management. As a data scientist in the renewable industry, you will work closely with engineers, O&M, Software/IT, and business stakholders to support or co-lead the development of data infrastructure (e.g., data warehousing) necessary to ingest telemetry and operational data from PV and BESS sites. You will integrate these datasets with enterprise platforms including accounting, CRM/ERP, CMMS, and satellite weather data providers to drive meaningful analytics, streamline reporting pipelines, and implement AI-driven solutions.

Key Responsibilities:

• Extract, process, and analyze large-scale datasets related to solar and energy storage power plant performance, predictive modeling, and operational forecasting.
• Collaborate with performance engineers to develop predictive models and analytics to forecast power plant performance and troubleshoot underperforming PV and BESS systems, identify potential component failures and modeling issues, and recommend corrective actions to meet guaranteed capacity and energy production targets.
• Work closely with cross-functional teams to develop data-driven strategies that drive operational and cost efficiencies.
• Utilize APIs to enable data extraction from various sources such as Data Acquisition System (DAS), equipment manufacturers (e.g. inverter, transformers, weather stations), National Weather Services (NOAA), and third-party weather data providers, etc.
• Develop and maintain ETL and ELT processes to structure and prepare data using SQL and related cloud-native tools.
• Lead the development of automation scripts and code for internal and external performance reporting.
• Engage with stakeholders to define data analysis needs, model development goals, and performance optimization objectives, ensuring the delivery of actionable insights.
• Present data-driven findings and recommendations to both technical and non-technical stakeholders to enable clarity and business impact.

Qualifications & Skills:

• Minimum 5 years of experience bridging performance engineering and data science, with at least 2 years spearheading cross-functional data science initiatives.
• Master's degree in a relevant field, such as computer science, data science, math, physics, and/or engineering such as electrical 
• Strong proficiency in Python, R, and SQL for data analysis, modeling, and automation.
• Hands-on experience with business intelligence and analytics tools such as Power BI, Tableau, NumPy, or Hex.
• Proficiency in leveraging Generative AI tools (e.g., Claude Code) and Large Language Models (LLMs) to accelerate code development, automate data processing workflows, and streamline complex analytics.
• Practical experience working in cloud platforms (e.g., AWS, Azure). Advanced skills in Microsoft Excel, including VBA and macros.
• Proven ability to work with real-world time-series data across the full data science lifecycle - from data collection and cleaning to model development, validation, and result communication.
• Demonstrated experience in data mining, feature engineering, and predictive analytics.
• Strong critical thinking skills and ability to work independently and as part of a team.

Preferred/Nice to Have:

• Experience working in the power industry, specifically in performance analysis and modeling (e.g. pvlib, SAM, PVSyst).
• Experience in conducting performance evaluation of PV plant performance testing by using standards such as ASTM and IEC.
• Demonstrated track record of designing and deploying AI-driven workflows to enhance predictive modeling, automate repetitive processes, and drive operational efficiencies.
• Knowledge of machine learning algorithms and statistical methods.
• Knowledge of SCADA and DAS (e.g. AlsoEnergy, GPM, Powerfactors, Ignition, Wattch, Denowatts, SynaptiQ, PI System, etc.) and CMMS (Fiix, Maximo, Sitetracker, Softwrench).
• PMP or other project management certification.