Job Title: Data Science Expert
Job Purpose
The Data Science Expert leads and develops high-performing teams of data scientists and data engineers to deliver advanced analytics, AI, and predictive modeling solutions for ENEC’s nuclear operations. This role ensures technical excellence, compliance with nuclear safety standards, and the delivery of actionable insights that optimize plant performance, fuel cycle management, and operational reliability. The Expert acts as a strategic advisor, technical authority, and mentor, driving innovation and embedding analytics into the core of ENEC’s mission.
Key Activities, Responsibility & Accountability
Responsibilities
• Strategic Leadership:
Drive the data science and analytics strategy for nuclear operations, ensuring alignment with ENEC’s safety, reliability, and business objectives.
• Technical Excellence:
Oversee the design, development, and deployment of advanced models for reactor performance, fuel cycle optimization, outage prediction, and anomaly detection.
• Team Leadership:
Lead, mentor, and develop multidisciplinary teams of data scientists and engineers, fostering a culture of innovation, collaboration, and continuous improvement.
• Stakeholder Engagement:
Collaborate with plant, fuel, engineering, and regulatory teams to embed analytics into operational workflows and decision-making.
• Governance & Compliance:
Ensure all analytics activities adhere to nuclear safety culture, regulatory requirements, and robust data governance.
• Operational Excellence:
Monitor and improve the impact of analytics on plant reliability, fuel efficiency, and business outcomes.
• Expert Knowledge Application:
Apply advanced expertise in statistical modeling, machine learning, and AI to develop solutions for complex nuclear analytics challenges, ensuring technical rigor and industry compliance.
• Complex Problem Solving:
Lead the resolution of ambiguous and high-impact analytics issues by designing innovative approaches, conducting root cause analysis, and implementing corrective/preventive actions to enhance operational reliability.
• Professional Know-How:
Utilize deep technical know-how to architect, validate, and deploy digital twins, predictive maintenance models, and fuel cycle optimization tools, ensuring best practices in MLOps and automation.
Responsibilities & Accountabilities (contd.)
Responsibilities and Accountabilities:
• Define, communicate, and continuously refine the analytics vision and multi-year roadmap for nuclear operations.
• Advise executive leadership on leveraging AI and advanced analytics for plant optimization, fuel cycle management, and operational excellence.
• Lead the development of business cases for analytics investments focused on nuclear plant performance, predictive maintenance, and fuel efficiency.
• Align analytics initiatives with ENEC’s digital transformation, safety culture, and national mission.
• Monitor industry trends and emerging technologies to ensure ENEC remains at the forefront of nuclear analytics.
Responsibilities and Accountabilities:
• Direct the design, development, and deployment of advanced statistical, machine learning, and AI models for nuclear plant operations, fuel cycle analysis, and safety-critical predictions.
• Oversee the development and validation of digital twins, predictive maintenance models, and fuel consumption forecasting tools.
• Ensure all models are validated against nuclear industry standards, regulatory requirements, and plant-specific constraints.
• Lead the adoption of MLOps best practices for continuous monitoring, retraining, and governance of models deployed in nuclear environments.
• Drive the adoption of automation, CI/CD pipelines, and advanced monitoring for analytics operations.
• Lead technical reviews, audits, and assurance activities to maintain high standards of quality, reliability, and compliance.
• Ensure robust documentation, explainability, and auditability of all models and analytics solutions
Professional Certifications
Relevant certifications in AI/ML, MLOps, and Data Governance.
Qualifications
Min - Master’s degree in data science, computer science, engineering, or related discipline. Proven experience leading data science teams in regulated environments
Pref - PhD or equivalent. Experience in nuclear, energy, or highly regulated sectors.
Experience
8 years of relevent experience
