Data Analyst

Job Description Summary GE Vernova’s Power Conversion & Storage business is at the forefront of the energy transition. We are seeking several highly skilled Data Analyst to join our teams to design, develop, and deliver AI-driven solutions that improve efficiency and decision-making across our business. In this role, you will collaborate closely with domain experts and cross-functional teams to apply artificial intelligence, generative AI, and machine learning to real-world industrial challenges, helping accelerate innovation, productivity, and operational excellence. A defining part of the role is technical judgment; choosing the right tool for each problem: classical machine learning, deep learning, GenAI, or pure software development when needed. Job Description Key ResponsibilitiesAI & ML Solution Development & IntegrationDesign, develop, and implement AI solutions, including generative AI, machine learning models, neural networks, and optimization algorithms, to improve business process efficiency and effectiveness. Select the appropriate modelling approach for each problem and articulate the trade-offs behind that choice. Own the machine learning lifecycle: dataset construction, metrics definition, acceptance criteria in accordance with the stakeholders needs, evaluation strategies. Translate business and operational needs into scalable AI-enabled tools, applications, and workflows. Support the deployment and integration of AI/ML models into existing business and technical systems, software environments, and products where applicable, including monitoring for drift, performance degradation, and running cost.  Technical Implementation & ArchitectureCollaborate with domain experts to identify high-value use cases and define technical requirements for AI solutions. Define and document the solution architecture end to end: from data sources to the integration with the existing enterprise and technical IT landscape. Design cloud-ready and on-premises solutions aligned with company IT, cybersecurity and data-governance standards. Integrate AI/ML capabilities into hardware, software, and business process ecosystems in a way that supports reliability, usability, and maintainability. Contribute to the development of robust, production-ready AI solutions suitable for industrial environments.  Solution Delivery, Partner & Contractor ManagementWrite clear technical specifications, statements of work, and acceptance criteria for work delivered by external contractors, software vendors, or internal digital teams. Contribute to supplier, platform, and tool selection through structured technical evaluation, benchmarking, and proof-of-concept comparison. Steer and review the work of internal & external partners: technical follow-up, design reviews, code and model reviews, quality gates, and acceptance testing; remaining the technical owner and guardian of the delivered solution.