Data Analyst

Job Description Summary

Ensure compliance with standards, continuous development of people and processes, effective management of budget and resource while insuring the team has the processes and tools they need to deliver on professional services project commitments. Impacts quality of own work and the work of others on the team. Executes standard operational/technical tasks typically subject to instructions and work routines. There is latitude to rearrange the sequence to complete task/duties based on changing work situations.

Job Description

Services Solution Line, Central Team, Data Analyst Engineer

DESCRIPTION:

The Services Business Data Analyst Engineer will be responsible for designing, implementing, and maintaining data management frameworks, including data collection, integration, storage, and governance.

The role focuses on transforming raw operational and service data into structured, reliable datasets and actionable insights to support the development of new services, digital products, and market opportunities.

The position ensures compliance with data standards, cybersecurity, and architectural guidelines while driving the continuous enhancement of analytical models, algorithms, and technical solutions. This includes improving data pipelines, model performance, scalability, and system reliability. The engineer also defines and optimizes processes, tools, and technical methodologies required for the successful execution of professional services projects, directly influencing the technical quality, robustness, and consistency of team deliverables.

MAIN RESPONSIBILITIES

• Work closely with product manager, service leaders, and process leaders to define advanced analytics and data strategies aligned with service objectives.
• Lead the integration, and analysis of large-scale operational, asset, and field data (equipment performance, maintenance, reliability, HSE, etc.).
• Drive the design and evolution of enterprise data models, data architectures, and analytics platforms supporting service operations.
• Lead or contribute significantly to the development of advanced AI/ML models, including predictive maintenance, failure forecasting, and root-cause analysis.
• Provide data-driven insights to improve asset reliability, service efficiency, cost optimization, and operational uptime.
• Define and recommend robust technical solutions for data management, including data governance, security, access control, scalability, and performance optimization.
• Ensure high data quality standards and establish best practices for data validation, monitoring, and lifecycle management.
• Translate complex analytical outputs into clear insights and recommendations for the engineering and operational leaders.
• Act as a key interface between service operations, engineering teams, IT, and AI/data science experts.
• Support decision-making for field operations through advanced dashboards, KPIs, and performance monitoring tools.
• Identify opportunities to leverage digital and AI technologies to enhance service delivery, predictive capabilities, and operational excellence.
• Contribute to the development of analytics capabilities and standards within the organization.
• Maintain a strong understanding of energy industry trends, asset lifecycle management, and service business drivers.
• Influence analytics and digital strategy by contributing expertise to cross-functional and leadership initiatives.
• Demonstrate strong leadership, communication, and stakeholder-management skills to drive adoption of analytics solutions across the organization.
• Act as a Service central team partner supporting regional service organizations by delivering standardized, high-impact data and analytics solutions.
• Broadening knowledge of own technical discipline to execute policy/strategy. May include support roles with specialized technical field of knowledge; still acquiring higher level knowledge and skills.
• A job at this level requires good interpersonal skills. Develop relationship with other team members and serves as the interface between operational teams and AI GE experts. Explains technical information to others.

• Support regional change management by promoting data-driven decision-making and adoption of analytics solutions.
• Contribute to continuous improvement initiatives by identifying opportunities to standardize and optimize service processes across regions.
• Participate in cross-functional projects related to digital transformation, service excellence, and operational performance.
• Stay current with emerging analytics, AI, and energy industry trends, and share best practices across the global service community.

• Possess a good knowledge and understanding in data science, statistics and mathematics
• Possess a good knowledge and understanding in Artificial Intelligence (Machine leaning, deep learning, language model ...)
• Ability to analyze and interpret complex data, think critically, and solve problems
• Good knowledge and understanding of IT (communication network, programming)
• Ability to present technical information and complex data to a non-expert audience
• Bachelor's degree from an accredited university or college (or a high school diploma with relevant experience).
• Possess excellent interpersonal skills when interfacing with internal and external customers
• Ability to multi-task
• Self-starter, ability to work remotely and achieve results with little direct supervision
• Proficiency in Microsoft Office
• Proficient written, verbal, and phone skills in English

• Team player in an international environment, adaptability, autonomy, resourcefulness and focus on customer service and problem solving
• Able to influence and gain commitment at all levels of the organization
• Strong organizational skills
• Engineering degree in Power electronics
• Experience in the utility market, particularly with FACTS and HVDC systems and associated equipment, is a plus
• Previous experience in related service business
• Able to travel by car (have a valid driver's license and ability to maintain) and/or air