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data science expert

Emirates Nuclear Energy

<div></div><div><div><div><div><div>Posting Date: 7 Jul 2026
</div></div></div></div><div><div><div><div>Requisition ID: 3584
</div></div></div></div><div><div><div><div>Location: HQ - Abu Dhabi
</div></div></div></div><div><div><div><div>Posting Status: Active Recruitment
</div></div></div></div><div><div><div><div><div><div><div><h2 class="jobSectionHeader"><b>Job Purpose</b></h2>
</div><div><p>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&rsquo;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&rsquo;s mission.</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>Key Activities, Responsibility &amp; Accountability</b></h2>
</div><div><div>Responsibilities
<br>
<ul><li>Strategic Leadership:
</li></ul>Drive the data science and analytics strategy for nuclear operations, ensuring alignment with ENEC&rsquo;s safety, reliability, and business objectives.
<br>
<ul><li>Technical Excellence:
</li></ul>Oversee the design, development, and deployment of advanced models for reactor performance, fuel cycle optimization, outage prediction, and anomaly detection.
<br>
<ul><li>Team Leadership:
</li></ul>Lead, mentor, and develop multidisciplinary teams of data scientists and engineers, fostering a culture of innovation, collaboration, and continuous improvement.
<br>
<ul><li>Stakeholder Engagement:
</li></ul>Collaborate with plant, fuel, engineering, and regulatory teams to embed analytics into operational workflows and decision-making.
<br>
<ul><li>Governance &amp; Compliance:
</li></ul>Ensure all analytics activities adhere to nuclear safety culture, regulatory requirements, and robust data governance.
<br>
<ul><li>Operational Excellence:
</li></ul>Monitor and improve the impact of analytics on plant reliability, fuel efficiency, and business outcomes.
<br>
<ul><li>Expert Knowledge Application:
</li></ul>Apply advanced expertise in statistical modeling, machine learning, and AI to develop solutions for complex nuclear analytics challenges, ensuring technical rigor and industry compliance.
<br>
<ul><li>Complex Problem Solving:
</li></ul>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.
<br>
<ul><li>Professional Know-How:
</li></ul>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.</div>
</div></div><div><div><h2 class="jobSectionHeader"><b>Responsibilities &amp; Accountabilities (contd.)</b></h2>
</div><div><p>Responsibilities and Accountabilities:</p>
<ul><li>Define, communicate, and continuously refine the analytics vision and multi-year roadmap for nuclear operations.
</li><li>Advise executive leadership on leveraging AI and advanced analytics for plant optimization, fuel cycle management, and operational excellence.
</li><li>Lead the development of business cases for analytics investments focused on nuclear plant performance, predictive maintenance, and fuel efficiency.
</li><li>Align analytics initiatives with ENEC&rsquo;s digital transformation, safety culture, and national mission.
</li><li>Monitor industry trends and emerging technologies to ensure ENEC remains at the forefront of nuclear analytics.
</li></ul>Responsibilities and Accountabilities:
<ul><li>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.
</li><li>Oversee the development and validation of digital twins, predictive maintenance models, and fuel consumption forecasting tools.
</li><li>Ensure all models are validated against nuclear industry standards, regulatory requirements, and plant-specific constraints.
</li><li>Lead the adoption of MLOps best practices for continuous monitoring, retraining, and governance of models deployed in nuclear environments.
</li><li>Drive the adoption of automation, CI/CD pipelines, and advanced monitoring for analytics operations.
</li><li>Lead technical reviews, audits, and assurance activities to maintain high standards of quality, reliability, and compliance.
</li><li>Ensure robust documentation, explainability, and auditability of all models and analytics solutions</li></ul>
</div></div><div><div><h2 class="jobSectionHeader"><b>Professional Certifications</b></h2>
</div><div><p>Relevant certifications in AI/ML, MLOps, and Data Governance.</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>Qualifications</b></h2>
</div><div><p>Min - Master&rsquo;s degree in data science, computer science, engineering, or related discipline. Proven experience leading data science teams in regulated environments</p>
<p>Pref - PhD or equivalent. Experience in nuclear, energy, or highly regulated sectors.</p>
</div></div><div><div><h2 class="jobSectionHeader"><b>Experience</b></h2>
</div><div><p>8 years of relevent experience</p></div></div></div></div></div></div></div></div><p></p>

Data Science Expert

ENEC Operations

<div>
 Job Title: Data Science Expert
 <br/>
 <br/>
 Posting Date: 7 Jul 2026
 <br/>
 <br/>
 Requisition ID: 3584
 <br/>
 <br/>
 Location: HQ - Abu Dhabi
 <br/>
 <br/>
 Posting Status: Active Recruitment
 <br/>
 <br/>
 <strong>
  Job Purpose
  <br/>
  <br/>
 </strong>
 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&rsquo;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&rsquo;s mission.
 <br/>
 <br/>
 Key Activities, Responsibility &amp; Accountability
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Strategic Leadership:
   <br/>
   <br/>
  </li>
 </ul>
 Drive the data science and analytics strategy for nuclear operations, ensuring alignment with ENEC&rsquo;s safety, reliability, and business objectives.
 <br/>
 <br/>
 <ul>
  <li>
   Technical Excellence:
   <br/>
   <br/>
  </li>
 </ul>
 Oversee the design, development, and deployment of advanced models for reactor performance, fuel cycle optimization, outage prediction, and anomaly detection.
 <br/>
 <br/>
 <ul>
  <li>
   Team Leadership:
   <br/>
   <br/>
  </li>
 </ul>
 Lead, mentor, and develop multidisciplinary teams of data scientists and engineers, fostering a culture of innovation, collaboration, and continuous improvement.
 <br/>
 <br/>
 <ul>
  <li>
   Stakeholder Engagement:
   <br/>
   <br/>
  </li>
 </ul>
 Collaborate with plant, fuel, engineering, and regulatory teams to embed analytics into operational workflows and decision-making.
 <br/>
 <br/>
 <ul>
  <li>
   Governance &amp; Compliance:
   <br/>
   <br/>
  </li>
 </ul>
 Ensure all analytics activities adhere to nuclear safety culture, regulatory requirements, and robust data governance.
 <br/>
 <br/>
 <ul>
  <li>
   Operational Excellence:
   <br/>
   <br/>
  </li>
 </ul>
 Monitor and improve the impact of analytics on plant reliability, fuel efficiency, and business outcomes.
 <br/>
 <br/>
 <ul>
  <li>
   Expert Knowledge Application:
   <br/>
   <br/>
  </li>
 </ul>
 Apply advanced expertise in statistical modeling, machine learning, and AI to develop solutions for complex nuclear analytics challenges, ensuring technical rigor and industry compliance.
 <br/>
 <br/>
 <ul>
  <li>
   Complex Problem Solving:
   <br/>
   <br/>
  </li>
 </ul>
 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.
 <br/>
 <br/>
 <ul>
  <li>
   Professional Know-How:
   <br/>
   <br/>
  </li>
 </ul>
 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.
 <br/>
 <br/>
 <strong>
  Responsibilities &amp; Accountabilities (contd.)
  <br/>
  <br/>
 </strong>
 Responsibilities and Accountabilities:
 <br/>
 <br/>
 <ul>
  <li>
   Define, communicate, and continuously refine the analytics vision and multi-year roadmap for nuclear operations.
  </li>
  <li>
   Advise executive leadership on leveraging AI and advanced analytics for plant optimization, fuel cycle management, and operational excellence.
  </li>
  <li>
   Lead the development of business cases for analytics investments focused on nuclear plant performance, predictive maintenance, and fuel efficiency.
  </li>
  <li>
   Align analytics initiatives with ENEC&rsquo;s digital transformation, safety culture, and national mission.
  </li>
  <li>
   Monitor industry trends and emerging technologies to ensure ENEC remains at the forefront of nuclear analytics.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Responsibilities And Accountabilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   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.
  </li>
  <li>
   Oversee the development and validation of digital twins, predictive maintenance models, and fuel consumption forecasting tools.
  </li>
  <li>
   Ensure all models are validated against nuclear industry standards, regulatory requirements, and plant-specific constraints.
  </li>
  <li>
   Lead the adoption of MLOps best practices for continuous monitoring, retraining, and governance of models deployed in nuclear environments.
  </li>
  <li>
   Drive the adoption of automation, CI/CD pipelines, and advanced monitoring for analytics operations.
  </li>
  <li>
   Lead technical reviews, audits, and assurance activities to maintain high standards of quality, reliability, and compliance.
  </li>
  <li>
   Ensure robust documentation, explainability, and auditability of all models and analytics solutions
   <br/>
   <br/>
  </li>
 </ul>
 Professional Certifications
 <br/>
 <br/>
 Relevant certifications in AI/ML, MLOps, and Data Governance.
 <br/>
 <br/>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 Min - Master&rsquo;s degree in data science, computer science, engineering, or related discipline. Proven experience leading data science teams in regulated environments
 <br/>
 <br/>
 Pref - PhD or equivalent. Experience in nuclear, energy, or highly regulated sectors.
 <br/>
 <br/>
 <strong>
  Experience
  <br/>
  <br/>
 </strong>
 8 years of relevent experience
</div>


TMC Middle East

<div>
 <p>
  TMC Middle East is currently engaged in a project with one of our prestigious customers in UAE.
 </p>
 <p>
  We are seeking a highly capable Senior Data Scientist expert to help TMC to deliver this assignment.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   About the Role:
  </strong>
 </p>
 <p>
  Position: Senior Data Scientist
 </p>
 <p>
  Location: Abu Dhabi
 </p>
 <p>
  Experience: 8+ Years
 </p>
 <p>
  Preferred: Western &amp; Diverse candidates
 </p>
 <p>
  <br/>
 </p>
 <p>
  Technical Requirements
 </p>
 <p>
  ● Core AI/ML: Expert proficiency in Python and standard ML libraries (TensorFlow/PyTorch,
 </p>
 <p>
  Scikit-learn, Pandas, NumPy). Strong grasp of both supervised and unsupervised learning
 </p>
 <p>
  techniques.
 </p>
 <p>
  ● NLP &amp; LLMs: Deep experience with transformer-based models (GPT, BERT, Llama) and
 </p>
 <p>
  prompt engineering techniques (few-shot learning, fine-tuning) for domain-specific tasks.
 </p>
 <p>
  ● Data Engineering: Proficiency in handling complex data structures (JSON, XML) and
 </p>
 <p>
  familiarity with database querying (SQL/NoSQL) or graph data structures. Experience with
 </p>
 <p>
  data extraction from specialized formats is a significant plus.
 </p>
 <p>
  ● Backend Awareness: Understanding of how to expose models via RESTful APIs
 </p>
 <p>
  (Flask/FastAPI) and integrate them into larger software architectures.
 </p>
 <p>
  ● Statistics: Solid understanding of statistics, probability distribution, A/B testing. Adept at
 </p>
 <p>
  identifying and mitigating biases in datasets.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Professional Qualifications
 </p>
 <p>
  ● Experience: 5+ years of experience in Data Science or Machine Learning, with a proven
 </p>
 <p>
  track record of deploying models into production environments.
 </p>
 <p>
  ● Domain Adaptability: Ability to quickly grasp complex domain terminology (e.g.,
 </p>
 <p>
  construction regulations, defense standards, supply chain taxonomies) and translate them
 </p>
 <p>
  into logic.
 </p>
 <p>
  ● Structured Delivery: Experience working in structured delivery models
 </p>
 <p>
  (Agile/Sprint-based) while adhering to rigorous validation and verification standards.
 </p>
 <p>
  ● Collaboration: Strong communication skills to work effectively with Domain Experts,
 </p>
 <p>
  Backend Engineers, and Product Managers to align model outputs with real-world
 </p>
 <p>
  business logic.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Please share your CV with the title of
  <strong>
   Senior Data Scientist
  </strong>
 </p>
 <p>
  Mail ID : vigneshwari.sivalingam@tmc-employeneurs.com
 </p>
</div>


Senior Data Scientist

Abu Dhabi Agriculture and Food Safety Authority ADAFSA

<div>
 <p>
  <strong>
   About the Role
  </strong>
 </p>
 <p>
  We are seeking a highly skilled Expert in Bioinformatics &amp; AI to lead advanced computational analysis, machine learning model development, and genomic data interpretation. This role will support diagnostic innovation, pathogen surveillance, and AI-driven decision-making in a high-impact research and laboratory environment.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Design and implement bioinformatics pipelines for sequencing and molecular diagnostics.
  </li>
  <li>
   Develop and deploy machine learning and deep learning models for pathogen detection and predictive analytics.
  </li>
  <li>
   Perform genomic analyses including variant calling, phylogenetics, and taxonomic classification.
  </li>
  <li>
   Establish validation frameworks and quality assurance for AI/ML models.
  </li>
  <li>
   Manage databases, HPC infrastructure, and cloud resources.
  </li>
  <li>
   Ensure data security, integrity, and regulatory compliance.
  </li>
  <li>
   Translate complex data insights into actionable outputs for scientific teams.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Qualifications &amp; Experience
  </strong>
 </p>
 <p>
  <strong>
   Minimum Requirements
  </strong>
 </p>
 <ul>
  <li>
   Master&rsquo;s degree in Bioinformatics, Data Science, Computer Science, or related field.
  </li>
  <li>
   Minimum 5 years of experience in bioinformatics analysis.
  </li>
  <li>
   At least 2 years of experience in ML/DL model development in biological contexts.
  </li>
  <li>
   Experience in predictive modelling for diagnostics or outbreak response.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Preferred Qualifications
  </strong>
 </p>
 <ul>
  <li>
   PhD in Bioinformatics, Genomics, or Machine Learning.
  </li>
  <li>
   Experience with regulatory frameworks (ISO, GLP, AI governance).
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Skills &amp; Competencies
  </strong>
 </p>
 <p>
  <strong>
   Technical Skills
  </strong>
 </p>
 <ul>
  <li>
   Programming: Python, R, Bash
  </li>
  <li>
   Bioinformatics tools and genomic databases
  </li>
  <li>
   Machine learning frameworks (TensorFlow, PyTorch, etc.)
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Core Competencies
  </strong>
 </p>
 <ul>
  <li>
   Analytical thinking and modelling rigor
  </li>
  <li>
   Problem-solving and troubleshooting
  </li>
  <li>
   Effective communication of complex data
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Why Join Us
  </strong>
 </p>
 <ul>
  <li>
   Work at the intersection of AI and life sciences
  </li>
  <li>
   Contribute to cutting-edge genomic and diagnostic innovation
  </li>
  <li>
   Be part of a high-performance, research-driven environment.
  </li>
 </ul>
</div>


Expert in Bioinformatics & AI (خبير المعلوماتية الحيوية)

Discovered MENA

<div>
 <p>
  📍
  <strong>
   Location:
  </strong>
  Muscat, Oman (relocation support will be provided)
 </p>
 <p>
  💼
  <strong>
   Job Title:
  </strong>
  Senior Machine Learning Engineer
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
  We are looking for an ML powerhouse to join us in beautiful Muscat! If you&rsquo;re a Senior ML Engineer who loves getting under the hood of high-performance computing (HPC) and hardware acceleration to solve massive business challenges, we want to chat. ?
 </p>
 <p>
  <br/>
 </p>
 <p>
  ?
  <br/>
  This isn't just about building models; it&rsquo;s about leading the charge on design, optimization, and deployment at scale. You&rsquo;ll be our go-to expert for turning complex problems into sleek, AI-driven realit
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   y.
   <br/>
   What you&rsquo;ll be doi
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    ng:Building the Engi
   </strong>
   ne: Architecting production-ready ML pipelines from scratch&mdash;from training all the way to deployme
  </li>
  <li>
   <strong>
    nt.Pushing Limi
   </strong>
   ts: Optimizing workloads using CUDA, cuDNN, and Nvidia TensorRT to make sure everything runs lightning-fa
  </li>
  <li>
   <strong>
    st.The Heavy Lifti
   </strong>
   ng: Doing the deep-dive data analysis and feature engineering needed for top-tier datase
  </li>
  <li>
   <strong>
    ts.Leading the Pa
   </strong>
   ck: Mentoring junior engineers, heading up code reviews, and making sure we&rsquo;re always following best practic
  </li>
  <li>
   <strong>
    es.Collaborati
   </strong>
   ng: Working closely with stakeholders to turn business needs into technical wi
  </li>
  <li>
   <strong>
    ns.Staying Sha
   </strong>
   rp: Keeping us on the cutting edge by staying obsessed with the latest AI/ML advancemen
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  ts.
  <strong>
   <br/>
   🔍 We're looking for someone w
  </strong>
 </p>
 <ul>
  <li>
   ith:5+ years of hands-on experience developing and deploying ML mod
  </li>
  <li>
   els.A pro with Python, TensorFlow, and PyTo
  </li>
  <li>
   rch.Experience with tools like MLflow or Kubef
  </li>
  <li>
   low.Advanced skills in Docker, REST APIs, and
  </li>
  <li>
   Git.Someone who knows their way around Nvidia Nsight, PyTorch Profiler, or Tensorboard for optimizat
  </li>
  <li>
   ion.Experience deploying AI solutions on AWS, GCP, or Az
  </li>
  <li>
   ure.Strong leadership vibes and the ability to explain "techy" things to non-techy peo
  </li>
  <li>
   ple.A Bachelor&rsquo;s or Master&rsquo;s in Computer Science, Data Science, or a related fi
  </li>
 </ul>
 <p>
  <br/>
 </p>
 eld.
</div>


Senior Machine Learning Engineer

<div>
 <p>
  <strong>
   Senior Manager of AI Safety and Validation Engineering
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Location:
  </strong>
  Abu Dhabi
 </p>
 <p>
  <strong>
   Duration:
  </strong>
  Permanent
 </p>
 <p>
  <strong>
   Package:
  </strong>
  45k-50k AED per month, TAX FREE + Relocation &amp; benefits
 </p>
 <p>
  <br/>
 </p>
 <p>
  Discover the opportunity
 </p>
 <p>
  We are hiring a Senior Manager of AI Safety and Validation Engineering to join a leading bank in their Group Business Services division. This is primarily a technical practitioner role focused on the design and implementation of technical measures to ensure the reliability and security of advanced AI solutions. You will bridge the gap between cutting edge AI development and rigorous risk standards while serving as a technical liaison to second line risk functions
 </p>
 <p>
  <br/>
 </p>
 <p>
  Discover the role
 </p>
 <p>
  As a Senior Manager of AI Safety and Validation Engineering, you will lead the creation of evaluation frameworks for both predictive Machine Learning and Generative AI. You will be responsible for defining standardised monitoring protocols and automated guardrails. Working as an individual contributor, you will provide hands on execution support to various product teams to ensure all deployments meet high performance and compliance standards.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Discover the responsibilities
 </p>
 <ul>
  <li>
   Define standardised evaluation rubrics and scoring systems for system performance and safety across various AI archetypes including RAG and agentic workflows
  </li>
  <li>
   Design comprehensive test cases covering deterministic logic and adversarial scenarios to stress test AI outputs
  </li>
  <li>
   Implement automated evaluators such as LLM-as-a-judge and targeted small language models Deploy explainability techniques like Shapley Values and Integrated Gradients to ensure model transparency and unfair bias detection in lending and fraud models
  </li>
  <li>
   Partner with platform teams to build telemetry pipelines that capture embeddings and inputs while maintaining strict data privacy standards
  </li>
  <li>
   Establish golden signals such as hallucination rates and semantic similarity to trigger automated circuit breakers when performance thresholds are breached
  </li>
  <li>
   Analyse guardrail violations to identify emerging attack patterns and integrate human-in-the-loop corrections into model refinement cycles
  </li>
  <li>
   Translate technical telemetry into actionable model health reports for second-line risk functions Work with specialist software vendors to bring advanced safety capabilities into the internal AI ecosystem
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  Discover the requirements
 </p>
 <ul>
  <li>
   7+ years of experience in Machine Learning Engineering, Data Science, or AI Safety and Testing
  </li>
  <li>
   Bachelor&rsquo;s Degree in Computer Science, Information Technology, or a related engineering discipline
  </li>
  <li>
   Expert proficiency in Python and deep knowledge of statistical testing and XAI libraries
  </li>
  <li>
   Hands-on experience with LLM evaluation frameworks such as Ragas, Giskard, or Arize
  </li>
  <li>
   Proven ability to design observability and monitoring systems at scale
  </li>
  <li>
   Prior experience in the financial sector is highly preferred
  </li>
  <li>
   Strong leadership skills with the ability to act as a technical mentor across cross-functional initiatives
  </li>
 </ul>
 <p>
 </p>
</div>


Senior Manager of AI Safety and Validation Engineering

<div>
 <p>
  The Data and AI Engineering Expert is a senior hands-on technical authority responsible for the design, development, and operationalization of enterprise data and AI platforms across ENEC. This role leads the engineering delivery of scalable, secure, and compliant data pipelines, AI/ML solutions, and analytics platforms leveraging technologies such as Databricks (Delta Lake, Unity Catalog, MLflow, Delta Live Tables), Microsoft Azure (Azure Data Factory, Azure ML, Microsoft Fabric, Azure AI Foundry, Copilot Studio), Collibra (Data Governance &amp; Data Quality), Power BI, and OT/industrial data systems including PI System, SCADA, and DCS.
 </p>
 <p>
  <br/>
 </p>
 <p>
  The Expert applies deep engineering expertise to architect and deliver production-grade solutions, ensures data governance and quality standards are upheld, and drives the adoption of AI and analytics capabilities that directly support ENEC's mission of safe, innovative, and efficient nuclear energy generation. This role acts as a principal technical contributor and mentor, enabling operational excellence and digital transformation at scale.
 </p>
 <p>
  Activity: Data Engineering Architecture &amp; Platform Development
 </p>
 <p>
  <br/>
 </p>
 <p>
  Responsibilities and Accountabilities:
 </p>
 <p>
  &bull; Design, build, and maintain scalable, secure, and high-performance data platforms including Lakehouse architectures using Databricks Delta Lake, Unity Catalog, and Delta Live Tables (DLT).
 </p>
 <p>
  &bull; Develop and operationalize robust data pipelines, ETL/ELT workflows, and integration frameworks using Azure Data Factory, Databricks Workflows, and related orchestration tools.
 </p>
 <p>
  &bull; Architect and implement data models, semantic layers, and data products that serve enterprise analytics, AI, and reporting needs.
 </p>
 <p>
  &bull; Ensure seamless integration of OT and industrial data sources &mdash; including PI System, SCADA, and DCS &mdash; into enterprise data platforms.
 </p>
 <p>
  &bull; Design and implement APIs, data contracts, and integration frameworks to enable enterprise-wide data consumption.
 </p>
 <p>
  &bull; Ensure platform scalability, resilience, high availability, and disaster recovery capabilities in compliance with nuclear and regulatory requirements.
 </p>
 <p>
  &bull; Apply and enforce data standards, naming conventions, and metadata management practices across all data assets using Collibra and Unity Catalog.
 </p>
 <p>
  Responsibilities and Accountabilities:
 </p>
 <p>
  &bull; Design, develop, and deploy production-grade machine learning, deep learning, and generative AI models using Azure ML, MLflow, and Databricks ML.
 </p>
 <p>
  &bull; Engineer end-to-end MLOps pipelines covering model training, versioning, validation, deployment, monitoring, and retraining &mdash; ensuring reliability and reproducibility.
 </p>
 <p>
  &bull; Build and operationalize AI-powered solutions including predictive analytics, anomaly detection, natural language processing (NLP), and GenAI/LLM-based applications using Azure AI Foundry and Copilot Studio.
 </p>
 <p>
  &bull; Develop BI and semantic models in Microsoft Fabric and Power BI, enabling self-service analytics and executive reporting across the organization.
 </p>
 <p>
  &bull; Apply Responsible AI principles and governance frameworks to all AI and ML solutions, ensuring explainability, fairness, and compliance.
 </p>
 <p>
  &bull; Conduct rigorous model evaluation, performance benchmarking, and validation to ensure solutions meet accuracy, reliability, and safety standards.
 </p>
 <p>
  &bull; Contribute to the continuous improvement of AI engineering standards, patterns, and reusable components across the enterprise.
 </p>
 <p>
  Activity: Advanced Subject Matter Knowledge
 </p>
 <p>
  <br/>
 </p>
 <p>
  Responsibilities and Accountabilities:
 </p>
 <p>
  &bull; Demonstrates deep, hands-on expertise in enterprise data engineering, AI/ML platform development, and cloud-native architectures within highly regulated environments.
 </p>
 <p>
  &bull; Maintains current knowledge of global trends in data engineering, MLOps, GenAI, cloud technologies (Azure, hybrid, on-premise), and nuclear industry compliance requirements.
 </p>
 <p>
  &bull; Understands the full lifecycle of data and AI platforms including design, development, testing, deployment, monitoring, and decommissioning.
 </p>
 <p>
  &bull; Applies comprehensive knowledge of data governance frameworks (Collibra, Unity Catalog), master data management, data quality, and lineage management.
 </p>
 <p>
  &bull; Possesses strong awareness of OT/IT convergence, industrial data systems (PI System, SCADA, DCS), and their integration into enterprise analytics environments.
 </p>
 <p>
  &bull; Maintains expert-level proficiency in programming languages and frameworks including Python, SQL, Spark, and relevant AI/ML libraries.
 </p>
 <p>
  Activity: Complex Problem Solving &amp; Innovation
 </p>
 <p>
  <br/>
 </p>
 <p>
  Responsibilities and Accountabilities:
 </p>
 <p>
  &bull; Tackles complex, ambiguous engineering challenges in data platform architecture, AI model development, and system integration &mdash; delivering innovative, compliant, and production-ready solutions.
 </p>
 <p>
  &bull; Leads root cause analysis and corrective/preventive actions for platform incidents, data quality failures, model degradation, and system disruptions.
 </p>
 <p>
  &bull; Develops and implements robust engineering solutions to address performance bottlenecks, scalability constraints, and integration challenges.
 </p>
 <p>
  &bull; Navigates conflicting technical requirements, evolving regulatory standards, and stakeholder needs to deliver optimal engineering outcomes.
 </p>
 <p>
  &bull; Drives continuous improvement by benchmarking against global engineering best practices, evaluating emerging technologies, and implementing lessons learned.
 </p>
 <p>
  &bull; Leads proof-of-concept and pilot initiatives to evaluate new data and AI technologies and engineering approaches
 </p>
 <p>
  <br/>
 </p>
 <p>
  Activity: Applied Skills &amp; Professional Know-How
 </p>
 <p>
  <br/>
 </p>
 <p>
  Responsibilities and Accountabilities:
 </p>
 <p>
  &bull; Expertly engineers, deploys, and operates scalable, secure, and compliant data and AI platforms across Databricks, Azure, and OT environments.
 </p>
 <p>
  &bull; Applies hands-on proficiency in building data pipelines, ML models, GenAI solutions, BI semantic models, and governance frameworks in production environments.
 </p>
 <p>
  &bull; Mentors and develops junior and mid-level data engineers, data scientists, and analytics engineers &mdash; building future-ready technical capabilities.
 </p>
 <p>
  &bull; Leads technical design reviews, code reviews, and architecture assessments to uphold engineering quality and best practices.
 </p>
 <p>
  &bull; Effectively translates complex technical concepts into clear, actionable insights for both technical and non-technical stakeholders.
 </p>
 <p>
  &bull; Documents solutions, engineering patterns, and technical standards to build institutional knowledge and enable knowledge transfer.
 </p>
 <p>
  Activity: Security, Governance &amp; Compliance
 </p>
 <p>
  <br/>
 </p>
 <p>
  Responsibilities and Accountabilities:
 </p>
 <p>
  &bull; Design and enforce data security, access control, and privacy frameworks across all data and AI platforms using Unity Catalog, Collibra, and Azure security controls.
 </p>
 <p>
  &bull; Ensure all data engineering and AI solutions comply with national and international nuclear regulations, FANR requirements, and Responsible AI principles.
 </p>
 <p>
  &bull; Maintain comprehensive data lineage, audit trails, and documentation to support regulatory, audit, and governance requirements.
 </p>
 <p>
  &bull; Implement and enforce data quality frameworks and data governance policies using Collibra Data Quality and Unity Catalog.
 </p>
 <p>
  &bull; Conduct regular platform security assessments, data quality audits, and compliance reviews.
 </p>
 <p>
  &bull; Oversee risk management, audit readiness, and the implementation of robust technical controls for all platform operations.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Minimum
  </strong>
 </p>
 <p>
  &bull; Bachelor&rsquo;s degree in computer science, Information Technology, Data Management, Engineering, or related discipline.
 </p>
 <p>
  &bull; Minimum 12+ years' hands-on experience in enterprise data engineering, AI/ML platform development, and cloud-native architectures, including production deployment and operations.
 </p>
 <p>
  &bull; Experience embedding governance within modern data platforms (preferably Databricks) and integrating SAP/Oracle ERP domains.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Preferred
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  &bull; Master&rsquo;s degree in a relevant field.
 </p>
 <p>
  &bull; Experience in energy, utilities, nuclear, financial services, government, or other highly regulated sectors.
 </p>
 <p>
  &bull; Demonstrated AI governance experience (provenance, bias monitoring, model data requirements) in data bricks or similar AI/analytics platforms exposure.
 </p>
 <p>
  &bull; Demonstrated experience leading large-scale data and AI engineering programs
 </p>
 <p>
  <br/>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Certification -
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  Multiple cloud and AI certifications. Microsoft Fabric, Azure AI Foundry, or Databricks Unity Catalog specialty certifications. Industry publications or contributions in data engineering or AI.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Relevant certifications in one or more of: Databricks (Data Engineer Associate/Professional, ML Professional), Microsoft Azure (Data Engineer, AI Engineer, Solutions Architect), MLOps, or Data Governance (Collibra).
 </p>
</div>


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