Data Analyst 

Company Overview 

LG Energy Solution Vertech, Inc. (LGES Vertech) is a full-service energy storage system supplier and integrator. Using our core strengths of expert service to our customers, unparalleled safety, and excellence in manufacturing, we bring standardized, fully integrated energy storage systems to a rapidly growing worldwide market. Our systems address our customers' needs to reduce capital equipment and installation costs while enhancing system-level performance and reliability using automated monitoring systems and analytics across the battery, power conditioning, and auxiliary systems.  Our AEROS® energy operating system is the engine of innovation to provide advanced control functions, allowing our customers to maximize the value of their energy storage assets.  Our service capabilities include advanced monitoring and analytics, scheduled maintenance, augmentation, and auxiliary system upgrades.  The combination of excellence in battery technology and production, coupled with nearly two decades of energy storage integration, makes LGES Vertech a supplier and integrator in the power and energy markets.

LGES Vertech empowers and expects its team members to assume responsibility and make good decisions while maintaining a team environment that fosters collaboration and innovation.  Our diverse and growing team enjoys competitive salaries, generous benefits, and flexible working hours.  

For more information about LGESVT, please visit www.lgensol-vt.com.  

Position Overview 

LGES-Vertech is seeking a highly motivated Data Analyst to join our Data Science and Predictive Analytics team, where you’ll be a key contributor in transforming data into actionable insights for Battery Energy Storage Systems (BESS). You will play a critical role in designing and delivering intuitive data visualizations, standardized reports, and data-driven storytelling that support both internal teams and external clients in understanding and optimizing storage system operations.

This role offers the opportunity to directly contribute to the development and continuous improvement of  our advanced asset analytics products, by creating scalable, user-focused reporting frameworks that enhance visibility into system performance, lifecycle trends, and operational health.

Key Responsibilities 

• Design, build, and maintain intuitive data visualizations and standardized reports that provide clear insights into system performance, usage patterns, and operational health of Battery Energy Storage Systems (BESS). 
• Translate complex datasets into compelling data stories that enable internal stakeholders and external clients to make informed, timely decisions. 
• Support the development and continuous improvement of the team’s advanced asset analytics products by creating scalable, user-friendly reporting frameworks. 
• Collaborate closely with data scientists, data engineers, and service teams to ensure that analytics outputs are accurate, reliable, and aligned with customer and business needs. 
• Develop and document reporting pipelines and visualization to improve consistency and reusability across projects and sites.
• Perform exploratory data analysis (EDA) and trend identification to uncover patterns, anomalies, and emerging issues that can inform product development and predictive models. 
• Deliver ad-hoc analyses and customized reports to support commissioning, operations, warranty management, and customer-facing performance reviews. 
• Apply statistical methods and basic forecasting techniques to support root cause investigations and provide early insights into performance deviations. 
• Continuously enhance dashboards and reporting capabilities by incorporating feedback from end users, adopting best practices in data storytelling, and leveraging new tools and technologies. 
• Communicate insights effectively across technical and non-technical audiences through visualizations, presentations, and written narratives 

.Job Requirements 

Required Qualifications: 

• Bachelor’s degree in Data Analytics, Computer Science, Engineering, Statistics, or a related quantitative field. 
• 2–5 years of hands-on expe