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 & Integration
  • Design, 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 & Architecture
  • Collaborate 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 Management
  • Write 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.
  • Ensure solutions remain maintainable after handover through documentation, knowledge transfer, and clearly assigned ownership, so that delivered tools do not become orphaned.
• Data Strategy & Analytics

• Lead or support the collection, processing, structuring, and analysis of large-scale operational and business data.
• Assess data readiness ahead of any development (availability, quality, labelling needs, access rights, confidentiality) and define strategies to close the gaps.
• Identify patterns, trends, and performance improvement opportunities using advanced analytics and AI methods.
• Develop data-driven solutions such as predictive maintenance, anomaly detection, quality and performance prediction, forecasting, cost analysis, document and requirement analysis, and knowledge support tools.