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GE Vernova · 2 weeks ago

Director of Data Analytics & Artificial Intelligence (AI) Solutions

United States

Full-time

Remote

Director/Executive

$152K/yr - $254K/yr

10+ years exp

GE Vernova is seeking a dynamic and results-driven Director of Data Analytics and Artificial Intelligence to lead their AI/ML strategy and team development. This role involves defining the direction of AI initiatives, building and mentoring a diverse team, and ensuring the development of scalable AI solutions that create business value.

EnergyEnergy EfficiencySustainability

Responsibilities

Develop and execute Grid Automation’s AI/ML strategy, aligning it with business goals to drive differentiation, efficiency, and growth

Build, mentor, and lead a diverse team of data scientists, machine learning engineers, and AI specialists, fostering a collaborative environment that promotes innovation and knowledge sharing

Act as the thought leader for AI/ML technology, staying up-to-date with industry trends, emerging technologies, and best practices

Drive innovation in AI methodologies, including deep learning, reinforcement learning, natural language processing (NLP), and computer vision

Oversee the design of robust machine learning pipelines and data workflows, ensuring seamless data ingestion, processing, and model deployment

Ensure that AI/ML solutions are scalable, efficient, and integrate seamlessly with existing systems and data infrastructure

Define and track key performance indicators (KPIs) for AI/ML models ensuring that solutions deliver business value and meet performance expectations

Monitor, maintain, and optimize deployed AI/ML models, ensuring continuous improvements in model accuracy and performance

Stay informed of regulatory requirements around data privacy, security, and ethics, ensuring that AI/ML solutions comply with all relevant standards and laws

Collaborate with product managers, engineering teams, and other functions to identify opportunities and define project scope, timelines, and deliverables for AI/ML projects

Foster an environment of continuous learning, encouraging the team to experiment with new algorithms, frameworks, and methodologies

Contribute to industry thought leadership by attending conferences and publishing papers

Qualification

AI/ML strategyMachine learning modelsData processing toolsTeam leadershipDeep learningNatural language processingCloud computingProgramming languagesEthical AI knowledgeInterpersonal skillsProblem-solving skillsCommunication skills

Required

Master's/PhD Degree in computer science, electrical engineering, or electric power engineering

10+ years of experience in AI/ML, including unsupervised learning, supervised learning, and reinforcement learning, large language models (LLMs)

Proven experience in developing, deploying, and scaling machine learning and AI models in production environments

Strong leadership, team management, and interpersonal skills with a track record of leading multidisciplinary, high-performing teams

Preferred

Strong expertise in algorithms, machine learning frameworks (e.g. TensorFlow, PyTorch, Scikit-learn), and data processing tools

Extensive knowledge of machine learning algorithms, deep learning, reinforcement learning, NLP, and computer vision

Excellent communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences

Strong problem-solving skills, with the ability to think strategically and execute on complex technical initiatives

Knowledge of ethical AI principles and data privacy regulations

Advanced experience in utilizing and applying common programming languages, such as Python, C/C++, Java, Spark and Hadoop, R Programming, Kafka, C#, MATLAB, along with good familiarity with power system modeling and data communication format

Experience with microservices architecture, containerization technologies (Docker, Kubernetes), and cloud computing platforms (AWS, Azure, Google Cloud)

Expertise in GraphDB, SQL/NoSQL, MS Access, databases

Knowledge of industrial automation or power system design

Published research or contributions to open-source AI/ML projects

Familiarity with energy industry standards and documentation procedures