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ai & advanced analytic specialist

ai advanced analytic specialist

atmaal

<div>
 
 AI &amp; Advanced Analytics Specialist .
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 &bull; Collaborate with business stakeholders to translate strategic objectives into data-driven solutions and advanced analytics use cases.
 
 
 &bull; Design and develop predictive models including forecasting, classification, regression, and customer segmentation.
 
 
 &bull; Apply machine learning and optimization techniques to generate actionable business recommendations.
 
 
 &bull; Utilize Natural Language Processing (NLP) techniques for sentiment analysis, text classification, and information extraction from unstructured data.
 
 
 &bull; Conduct exploratory data analysis to identify trends, anomalies, and opportunities for business improvement.
 
 
 &bull; Leverage Generative AI capabilities for intelligent automation, content summarization, code generation, and insight extraction.
 
 
 &bull; Develop and deploy analytical solutions using modern cloud-based platforms and AI services.
 
 
 &bull; Build interactive dashboards and visualizations that effectively communicate insights to both technical and non-technical stakeholders.
 
 
 &bull; Monitor, validate, and continuously improve analytical models to ensure performance and reliability.
 
 
 &bull; Maintain proper documentation, methodology standards, and reproducible analytics workflows.
 
 
 
 
 
 Requirements:
 
 
 
 
 
 &bull; Bachelor's degree in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, or a related field.
 
 
 &bull; 3&ndash;4 years of experience in Data Science, Advanced Analytics, Machine Learning, or Artificial Intelligence.
 
 
 &bull; Strong proficiency in Python.
 
 
 &bull; Hands-on experience with Power BI.
 
 
 &bull; Experience with Google Cloud Platform (GCP), including BigQuery, Vertex AI, and Google Cloud Storage.
 
 
 &bull; Practical experience in Machine Learning, Predictive Analytics, and NLP.
 
 
 &bull; Exposure to Generative AI technologies and Large Language Models (LLMs) is highly preferred.
 
 
 &bull; Strong analytical, problem-solving, and stakeholder management skills.
 
 
 
 
 
 Preferred Language Level:
 
 
 
 
 
 &bull; Professional working proficiency in English (written and verbal).
 
</div>

AI & Advanced Analytic Specialist

Maaden

<div>
 
 Job Purpose
 
 
 
 
 JOB DESCRIPTION
 
 
 
 <ul>
 <li>
 The Lead Specialist, Data Science &amp; Analytics, acts as a technical leader and senior practitioner, driving development, deployment, and scaling of Machine Learning, AI, and advanced analytics solutions across Maaden.
 </li>
 <li>
 The role ensures analytics products are designed, validated, industrialized, governed, and adopted at scale, providing measurable value across mining, processing, operations, and enterprise functions.
 </li>
 <li>
 Lead Specialist, Data Science &amp; Analytics is to analyze data, extract insights, and build predictive models that help organizations make smarter decisions and solve difficult problems. By blending expertise in statistics, computer science, and business strategy, they not only analyze complex datasets but also build predictive models that improve operations and shape long-term decisions. With nearly every industry leaning on data today, the demand for skilled professionals continues to grow
 
 
 </li>
 </ul>
 
 Key Accountabilities
 
 
 
 <ul>
 <li>
 Lead End-to-End Data Science Delivery
 </li>
 <li>
 Developing, implementing and maintaining databases and data collection systems
 </li>
 <li>
 Own the full lifecycle of ML/AI initiatives - from problem framing, data exploration, feature engineering, model development, validation, and MLOps handover.
 </li>
 <li>
 Deliver scalable and production-grade models, ensuring alignment with enterprise data governance and AI standards.
 </li>
 <li>
 Performing statistical analysis to understand and interpret data insights
 </li>
 <li>
 Applying data mining techniques to identify patterns, trends, and relationships in large datasets
 </li>
 <li>
 Building predictive models and machine learning algorithms to forecast future outcomes
 </li>
 <li>
 Creating clear data visualizations and reports to communicate findings to stakeholders
 </li>
 <li>
 Working with cross-functional teams to understand business needs and provide data-driven solutions
 </li>
 <li>
 Design and maintain reliable data pipelines and models in partnership with data engineering to ensure data is accurate, timely, and trustworthy for downstream use
 </li>
 <li>
 Ensuring data security and compliance with relevant regulations
 </li>
 <li>
 Drive experimentation, model versioning, automated retraining, and continuous improvement.
 </li>
 <li>
 Translate Business Needs into AI/Analytics Solutions
 </li>
 <li>
 Establish frameworks and operating models that make data science accessible, scalable, and embedded within business and technical functions
 </li>
 <li>
 Engage BU/domain stakeholders to identify value creation opportunities and convert them into actionable analytics use cases.
 </li>
 <li>
 Build value hypotheses, KPIs, success criteria, and solution roadmaps in collaboration with Data &amp; AI leadership and business teams.
 </li>
 <li>
 Industrialize AI/ML Models (ML Ops &amp; Architecture)
 </li>
 <li>
 Partner with data engineering, data platforms, and cloud/OT architecture teams to embed models into enterprise systems and operational layers.
 </li>
 <li>
 Set standards for production deployment, testing, monitoring, drift handling, and lifecycle governance.
 </li>
 <li>
 Ensure seamless integration of predictive and optimization models into enterprise platforms, control systems, and digital twins
 </li>
 <li>
 Leverage machine learning, optimization, and computer vision as enabling tools for performance, reliability, and sustainability improvements
 </li>
 <li>
 Responsible AI, Quality &amp; Governance
 </li>
 <li>
 Ensure compliance with Maaden&rsquo;s Responsible AI, data quality, and data governance frameworks.
 </li>
 <li>
 Promote reproducibility, documentation, lineage tracking, and auditability across all data science assets.
 </li>
 <li>
 Ensure transparency, explainability, and continuous model governance across production and enterprise environments
 </li>
 <li>
 Stakeholder Management &amp; Value Realization
 </li>
 <li>
 Communicate insights, results, risks, and recommendations to decision-makers using compelling narratives and visualization.
 </li>
 <li>
 Track value realization, adoption metrics, and operational impact to ensure measurable benefit.
 
 
 </li>
 </ul>
 
 Minimum Qualifications
 
 
 
 
 Minimum Qualification, Experience and Core Competencies:
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or related fields.
 
 
 </li>
 </ul>
 
 Minimum Experience
 
 
 
 Good to Have Capabilities
 
 
 <ul>
 <li>
 Minimum Experience:
 </li>
 <li>
 6+ years&rsquo; experience in Data Science / Advanced Analytics with industrial, mining, or heavy-asset environments preferred. Including at least 2 years leading or mentoring analytics professionals
 </li>
 <li>
 Proven ability to translate business problems into analytic approaches: define hypotheses, design analyses, and synthesize results into clear recommendations.
 </li>
 <li>
 Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch, Azure, AWS) &ndash; Microsoft AI Factory
 </li>
 <li>
 Strong technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering teams.
 </li>
 <li>
 Machine Learning &amp; Advanced Analytics
 </li>
 <ul>
 <li>
 Hands-on experience developing and deploying machine learning models, including time-series forecasting, predictive modeling, and optimization use cases
 </li>
 <li>
 Strong understanding of model performance, validation, stability, and business impact
 </li>
 </ul>
 <li>
 Generative AI &amp; AI Agents
 </li>
 <ul>
 <li>
 Practical experience with Generative AI solutions, including copilots, intelligent automation, and agent-based workflows
 </li>
 <li>
 Ability to embed GenAI capabilities into enterprise processes to improve decision-making and operational efficiency
 
 
 </li>
 </ul>
 </ul>
 Preferred Experience &amp; Platforms
 
 
 <ul>
 <li>
 Data Engineering (IT + OT)
 </li>
 <li>
 Experience designing and maintaining data pipelines across IT and OT environments
 </li>
 <li>
 Exposure to sensor data, streaming / real-time data processing, and industrial data sources
 </li>
 <li>
 Ability to collaborate with data engineering teams to ensure reliable, timely, and trusted data flows
 </li>
 <li>
 MLOps / AgentOps
 </li>
 <li>
 Experience in model deployment and lifecycle management, including:
 </li>
 <ul>
 <li>
 Transition from model development to production and scale
 </li>
 <li>
 Monitoring, retraining, versioning, and drift management
 </li>
 </ul>
 <li>
 Familiarity with automation and operationalization of ML/AI workloads
 </li>
 </ul>
 <ul>
 <li>
 Cloud &amp; Analytics Platforms
 </li>
 <li>
 Experience working with enterprise cloud platforms, preferably:
 </li>
 <ul>
 <li>
 Microsoft Azure Data Platform
 </li>
 <li>
 Databricks AI Platform
 </li>
 <li>
 Microsoft AI Foundry / Microsoft AI Factory
 </li>
 </ul>
 <li>
 Understanding of cloud-native architectures for scalable analytics and AI solutions
 
 </li>
 </ul>
 
 Core Competencies
 
 
 
 <ul>
 <li>
 Model Accuracy &amp; Reliability: Performance, drift stability, and operational uptime.
 </li>
 <li>
 Adoption &amp; Business Impact: Value realized, user adoption, integration success.
 </li>
 <li>
 Delivery Velocity: Timeliness of development cycles and deployment readiness.
 </li>
 <li>
 Compliance &amp; Quality: Alignment with Responsible AI, governance, and documentation standards.
 </li>
 </ul>
</div>

Lead Specialist, Data Science & Analytics II

Qiddiya Investment Company

<div>The Director - Customer AI &amp; Analytics will lead the strategy, governance, architecture, and delivery of customer data products, customer intelligence platforms, and AI-driven engagement capabilities across Qiddiya.
This role will establish Qiddiya&rsquo;s customer data foundation and enable advanced personalization, audience intelligence, loyalty analytics, revenue optimization, and AI-powered customer engagement across parks, entertainment venues, digital channels, hospitality, retail, ticketing, mobility, and future city services.
The role requires a highly strategic leader with deep expertise in customer data ecosystems, AI enablement, enterprise data platforms, and digital transformation, combined with strong stakeholder management and execution capabilities.
The successful candidate will work closely with Digital, Marketing, Commercial, Customer Experience, IT, Operations, Strategy, and Executive Leadership teams to position customer data as a strategic enterprise asset. 
Key Responsibilities
Customer Data Strategy &amp; Transformation<ul><li>
Define and lead Qiddiya&rsquo;s enterprise Customer Data &amp; AI strategy aligned with business growth, visitor experience, and digital transformation objectives.
</li><li>Establish the long-term roadmap for customer data products, customer intelligence, AI enablement, and monetization opportunities.
</li><li>Build a unified customer data vision across ticketing, CRM, loyalty, mobile applications, digital platforms, attractions, hospitality, retail, mobility, and operational ecosystems.
</li><li>Drive enterprise adoption of customer-centric decision-making and data-driven engagement models.</li></ul> 
Customer 360 &amp; Data Products<ul><li>
Lead the development and evolution of enterprise Customer 360 capabilities and customer master data architecture.
</li><li>Define and oversee customer data products enabling:
</li><li>Visitor insights and segmentation
</li><li>Personalization and recommendation engines
</li><li>Customer lifetime value analysis
</li><li>Revenue and conversion analytics
</li><li>Loyalty and engagement intelligence
</li><li>Cross-channel customer journey analytics
</li><li>Real-time audience intelligence
</li><li>Predictive behavior modeling
</li><li>Partner with Data Engineering and Platform teams to ensure scalable and secure customer data pipelines and architectures.
</li><li>Enable self-service analytics and business consumption of customer intelligence products.</li></ul> 
AI &amp; Advanced Analytics<ul><li>
Lead AI initiatives focused on customer engagement, personalization, operational intelligence, and business optimization.
</li><li>Identify and drive high-value AI use cases including:
</li><li>AI-powered personalization
</li><li>Recommendation engines
</li><li>Conversational AI and intelligent assistants
</li><li>Customer sentiment analysis
</li><li>Dynamic audience targeting
</li><li>Predictive analytics
</li><li>AI-driven campaign optimization
</li><li>Generative AI use cases for customer engagement
</li><li>Collaborate with BI, Data Science, MLOps, and Emerging Technology teams to operationalize AI solutions.
</li><li>Establish AI governance principles aligned with enterprise standards and responsible AI practices.
</li></ul>Leadership &amp; Organizational Development<ul><li>
Build and lead a high-performing Customer Data &amp; AI function within the Data Office.
</li><li>Mentor multidisciplinary teams across analytics, AI, customer intelligence, and data product domains.
</li><li>Foster a culture of innovation, experimentation, agility, and business value realization.
</li><li>Support enterprise data literacy and AI adoption initiatives.</li></ul> 
 
 
Requirements 
Required Experience<ul><li>
12+ years of experience in Data, Analytics, AI, Customer Intelligence, or Digital Transformation domains.
</li><li>Proven leadership experience in enterprise-scale customer data and AI initiatives.
</li><li>Strong experience in Customer 360, CDP, CRM analytics, personalization, and customer intelligence ecosystems.
</li><li>Experience leading large cross-functional programs involving business, technology, and data stakeholders.
</li><li>Strong understanding of modern cloud data platforms and AI/ML ecosystems.
</li></ul><ul><li>Experience in key consumer-oriented industries including Entertainment, Hospitality, Theme Parks, and Retail.</li><li>
Experience managing strategic vendors, implementation partners, and enterprise programs.</li></ul></div>

Director - Customer AI & Analytics

Salesforce

<div>To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
Job Category
Sales
Job Details
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn&rsquo;t a buzzword &mdash; it&rsquo;s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You&rsquo;re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.
About the Role &gt;&gt;
 
 
We're looking for a driven and consultative Account Executive to join our growing team, selling at the forefront of enterprise data and AI transformation. In this role, you'll focus on MuleSoft and Informatica &mdash; two of the industry's most powerful platforms for integration and data management &mdash; while partnering closely with the core Salesforce AE team to deliver a complete, connected solution to customers.
 
 
MuleSoft empowers organizations to integrate any application, data source, or system through API-led connectivity &mdash; breaking down silos and creating a unified digital foundation. Informatica brings enterprise-grade data management, quality, and governance to ensure that foundation is built on clean, reliable, and compliant data.
 
 
Together, these platforms are the backbone of Salesforce Agentforce &mdash; enabling businesses to deploy autonomous AI agents that actually work, because they're powered by trusted, connected data. As a specialist AE, you'll play a critical role in the broader account team, positioning MuleSoft and Informatica as the essential data infrastructure that makes AI transformation possible.
 
 
This is a unique opportunity to own a specialist sales motion, work alongside a world-class core AE team, and help enterprise customers build the foundation their AI ambitions depend on. 
 
What you will be doing &gt;&gt; 
 
Our Data Foundation Account Executives engage with existing customers and new leads. They develop strong, positive, trusted relationships with both key stakeholders and c-suite decision makers within their patch, and help customers realize value from their Salesforce investments. You will use your skills to develop opportunities, through both warm leads and whitespace prospecting.
<ul><li>Develop key customer stakeholder relationships and drive customer satisfaction at assigned accounts
</li><li>Assist with the development and execution of overall long-term strategy for the account, aligned to customer business objectives
</li><li>Coordinate internal resources to meet customer business needs
</li><li>Assist with account planning at assigned accounts, coordinating with Prime and Cloud sales resources to ensure strategic alignment
</li><li>Share both MuleSoft and Informatica value proposition for existing and/or new customers
</li><li>Drive growth within new and existing, assigned accounts
</li></ul>What you&rsquo;ll need to be successful &gt;&gt;
<ul><li>Significant full cycle sales experience with a proven track record of success
</li><li>Experience in selling technical platforms preferred
</li><li>Integration / API / Data Governance / Agents Orchestration and Automation Awareness
</li><li>Ability to strategize with a large extended team
</li></ul>Unleash Your Potential
When you join Salesforce, you&rsquo;ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we&rsquo;ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future &mdash; but to redefine what&rsquo;s possible &mdash; for yourself, for AI, and the world.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates&rsquo; resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that&rsquo;s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications &ndash; without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.</div>

Account Executive KSA - Data Foundation (MuleSoft + Informatica)

InnovationTeam

<div>InnovationTeam is a forward-thinking technology company specialized in delivering advanced AI-driven solutions for enterprises and government organizations. We are currently seeking a highly skilled AI Team Lead to join our team onsite in Saudi Arabia.
As an AI Team Lead at InnovationTeam, you will be responsible for leading the design, development, implementation, and delivery of end-to-end AI solutions across multiple domains, including Generative AI, machine learning, deep learning, data science, computer vision, NLP, intelligent automation, and enterprise AI systems.
This role is not limited to Generative AI. It requires a strong technical background across modern AI technologies, hands-on experience in building production-ready AI solutions, and the leadership capability to manage AI engineers, data scientists, ML engineers, and cross-functional delivery teams.
The ideal candidate is a strong technical leader who can translate business requirements into scalable AI solutions, manage project execution, guide technical teams, communicate with stakeholders, and ensure successful delivery of AI initiatives within scope, timeline, and quality standards.
At InnovationTeam, we value innovation, ownership, collaboration, and continuous learning. We provide a dynamic work environment where technical excellence, leadership, and business impact are highly recognized. 
Requirements 
We are seeking an experienced AI Team Lead to lead onsite AI delivery in Saudi Arabia. The role involves managing AI projects, supervising technical teams, designing AI architectures, developing enterprise-grade solutions, and ensuring successful deployment of AI systems into production.
The candidate should have strong experience in Generative AI, machine learning, deep learning, data science, AI solution architecture, MLOps/LLMOps, cloud deployment, and project management.
Key Responsibilities<ul><li>
Lead the AI team in designing, developing, and delivering enterprise AI solutions.</li><li>
Manage AI projects from requirement gathering to production deployment.</li><li>
Translate business needs into technical AI solution designs and implementation plans.</li><li>
Design and supervise solutions involving Generative AI, LLMs, RAG systems, AI agents, NLP, machine learning, deep learning, and computer vision.</li><li>
Lead data science initiatives, including data analysis, feature engineering, model development, evaluation, and optimization.</li><li>
Build and oversee end-to-end AI pipelines, including data ingestion, preprocessing, model training, inference, monitoring, and continuous improvement.</li><li>
Guide the implementation of machine learning and deep learning models using frameworks such as PyTorch, TensorFlow, Scikit-learn, and related tools.</li><li>
Supervise the development of AI agents, chatbots, recommendation systems, classification models, predictive analytics, and intelligent automation solutions.</li><li>
Define AI architecture, integration patterns, APIs, microservices, and deployment strategies.</li><li>
Ensure AI solutions are scalable, secure, reliable, cost-efficient, and production-ready.</li><li>
Collaborate with business stakeholders, product teams, data teams, software engineers, and cloud teams.</li><li>
Manage task allocation, technical reviews, project milestones, risks, and delivery timelines.</li><li>
Establish best practices for MLOps, LLMOps, model governance, model monitoring, documentation, and quality assurance.</li><li>
Support presales and client discussions by providing technical input, solution proposals, effort estimation, and feasibility assessments.</li><li>
Ensure AI solutions comply with security, privacy, governance, and responsible AI principles.</li><li>
Mentor and coach AI engineers, ML engineers, data scientists, and junior team members.</li><li>
Stay up to date with the latest developments in AI, machine learning, deep learning, Generative AI, cloud AI services, and enterprise AI platforms.</li></ul>
Required Skills &amp; Qualifications<ul><li>
Minimum 5 years of professional experience in AI, machine learning, data science, or related technology fields.</li><li>
Minimum 2&ndash;3 years of experience leading AI teams or managing AI solution delivery.</li><li>
Master&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Computer Engineering, or a related field.</li><li>
Strong hands-on experience in machine learning, deep learning, NLP, Generative AI, and data science.</li><li>
Solid understanding of LLMs, RAG architectures, AI agents, vector databases, prompt engineering, and model evaluation.</li><li>
Strong experience with Python and AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, LangChain, or LlamaIndex.</li><li>
Experience in building and deploying ML/DL models for real-world enterprise use cases.</li><li>
Strong understanding of supervised learning, unsupervised learning, classification, regression, clustering, recommendation systems, forecasting, and anomaly detection.</li><li>
Experience with data preparation, data quality assessment, feature engineering, model training, validation, testing, and performance monitoring.</li><li>
Strong software engineering knowledge, including REST APIs, microservices, Docker, Kubernetes, CI/CD, and Git.</li><li>
Experience deploying AI workloads on cloud platforms such as OCI, Azure, AWS, or GCP. OCI experience is preferred.</li><li>
Knowledge of MLOps and LLMOps practices, including model versioning, monitoring, retraining, evaluation, and deployment automation.</li><li>
Strong project management skills, including planning, estimation, risk management, stakeholder communication, and delivery tracking.</li><li>
Ability to communicate complex technical concepts clearly to business and technical stakeholders.</li><li>
Excellent problem-solving, analytical, leadership, and decision-making skills.</li><li>
Excellent command of English, both written and spoken.</li><li>
Willingness to work onsite in Saudi Arabia.</li></ul>
Nice to Have<ul><li>
Experience in government, healthcare, finance, telecom, or regulated enterprise environments.</li><li>
Experience with GPU-based model training and inference optimization.</li><li>
Experience with computer vision, OCR, document AI, speech AI, or multimodal AI systems.</li><li>
Experience with Azure OpenAI, Oracle AI Services, AWS Bedrock, Google Vertex AI, or similar enterprise AI platforms.</li><li>
Knowledge of AI governance, responsible AI, data privacy, cybersecurity, and compliance frameworks.</li><li>
Experience in presales, technical proposal preparation, and client-facing solution presentations.</li><li>
Arabic language skills are an advantage.</li></ul> 

Benefits 
<ul><li>
Opportunity to lead strategic AI initiatives in Saudi Arabia.</li><li>
Work on advanced AI solutions across Generative AI, machine learning, deep learning, and data science.</li><li>
Leadership role with direct impact on enterprise and government AI transformation projects.</li><li>
Collaborative and innovation-driven work environment.</li><li>
Competitive compensation package.</li><li>
Access to modern AI infrastructure, cloud platforms, and enterprise data environments.</li><li>
Professional growth, leadership development, and continuous learning opportunities.</li></ul></div>

AI Team Lead

Emdad By Elm

<div>
 
 
 Job Summary
 
 
 
 
 
 
 Responsible for
 
 integrating data from multiple technology systems,
 
 
 databases
 
 , and
 
 data warehouses
 
 , transforming d
 
 ata into actionable insights, and developing intelligent
 
 dashboards and
 
 analytics solutions that support executive decision-making
 
 . The role focuses on data visualization, automation,
 
 AI adoption
 
 , and continuous enhancement to improve technology performance and operational efficiency.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 
 <ul>
 <li>
 Integrate and consolidate data from enterprise systems, databases, APIs, and data warehouses to build reliable dashboards and reporting solutions.
 </li>
 <li>
 Design, develop, and continuously enhance dashboards using Microsoft Power BI, Tableau, or similar enterprise platforms.
 </li>
 <li>
 Build and maintain centralized dashboards that consolidate all technology metrics into a single source of truth, enabling detailed monitoring and executive decision-making.
 </li>
 <li>
 Analyze technology data to identify trends, risks, anomalies, and performance improvement opportunities by dashboards.
 </li>
 <li>
 Develop automation workflows to streamline reporting processes, reduce manual effort, and improve operational efficiency.
 </li>
 <li>
 Explore and implement AI-powered capabilities to enhance predictive analytics, intelligent reporting, and automated decision support.
 </li>
 <li>
 Work with technology teams to understand technical data structures and translate requirements into scalable analytics solutions.
 </li>
 <li>
 Support continuous improvement initiatives by identifying opportunities to enhance technology products, requests, and operational performance through data-driven insights.
 </li>
 <li>
 Design intelligent automation workflows that proactively detect issues, trigger alerts, generate AI-driven recommendations, and automatically assign actions to relevant stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 
 
 Education
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Information Systems, Information Technology, or a related field.
 </li>
 </ul>
 
 
 Certifications
 
 
 <ul>
 <li>
 
 Microsoft Power BI/ Tableau Certification
 
 </li>
 <li>
 
 SQL / Database Management Certification
 
 (Preferred)
 </li>
 <li>
 
 Data Analytics Certifications
 
 </li>
 <li>
 
 ITIL v4 Foundation
 
 (Preferred)
 </li>
 <li>
 
 AI / Machine Learning Fundamentals Certification
 
 (Preferred)
 </li>
 <li>
 
 Automation Platform Experience (Microsoft Power Automate, n8n, UiPath)
 
 (Preferred)
 </li>
 </ul>
 
 
 Experience
 
 
 <ul>
 <li>
 
 3&ndash;4 years of experience in Data Intelligence, dashboard development, enterprise data integration, automation workflows, and AI-enabled analytics solutions.
 
 </li>
 </ul>
 
 
 Skills
 
 
 <ul>
 <li>
 Advanced
 
 Microsoft Power BI / Tableau Development
 
 </li>
 <li>
 
 Data Visualization &amp; Dashboard Design
 
 </li>
 <li>
 
 Data Integration &amp; System Connectivity (APIs, Databases, Enterprise Systems)
 
 </li>
 <li>
 
 SQL, Data Modeling &amp; Data Warehouse Understanding
 
 </li>
 <li>
 
 Technical Data Analysis &amp; Executive Reporting
 
 </li>
 <li>
 
 Process Automation &amp; Workflow Optimization (Microsoft Power Automate / n8n / UiPath)
 
 </li>
 <li>
 
 AI Tools Adoption &amp; AI-driven Analytics
 
 </li>
 <li>
 Predictive Analytics &amp; Intelligent Reporting
 </li>
 </ul>
</div>

Technology Data Intelligence Specialist

VaporVM

<div><div>Date Posted: 11 June, 2026
</div><div>Industry: IT Services and IT Consulting
</div><div>Location: VaporVM</div></div>
 <div><h2 class="jobSectionHeader">Job Description:</h2>
<div><h1 class="jobSectionHeader">Senior HPC / Infrastructure Engineer</h1>
Location: Riyadh, Saudi Arabia
Employment Type: Full-Time
Experience: 10+ Years (Hands-On)
<h2 class="jobSectionHeader">Position Overview</h2>
We are seeking a highly experienced Senior HPC / Infrastructure Engineer with proven expertise in designing, deploying, and operating enterprise-scale High-Performance Computing (HPC) and AI infrastructure environments. This role is ideal for a hands-on technical leader who has built and managed production-grade HPC platforms, GPU clusters, Kubernetes ecosystems, and AI infrastructure from the ground up.
The successful candidate will play a critical role in architecting, optimizing, and maintaining mission-critical compute environments that support advanced AI/ML, data science, and high-performance workloads.
<h2 class="jobSectionHeader">Required Certifications</h2>
<ul><li>RHCE &ndash; Red Hat Certified Engineer (Active)</li>
<li>CKA &ndash; Certified Kubernetes Administrator (Active)</li>
</ul><h2 class="jobSectionHeader">Core Technical Expertise</h2>
<h3 class="jobSectionHeader">HPC &amp; NVIDIA AI Ecosystem</h3>
<ul><li>NVIDIA Base Command Manager (BCM)</li>
<li>NVIDIA AI Enterprise</li>
<li>NVIDIA GPU Operator &amp; Network Operator</li>
<li>NVIDIA NIM Inference Services</li>
<li>NVIDIA AI Blueprints</li>
<li>CUDA, GPU Drivers, and Performance Optimization</li>
</ul><h3 class="jobSectionHeader">Compute &amp; Container Platforms</h3>
<ul><li>Kubernetes (Architecture, Operations &amp; Scaling)</li>
<li>Slurm Workload Manager</li>
<li>Distributed Computing Environments</li>
</ul><h3 class="jobSectionHeader">Operating Systems</h3>
<ul><li>Red Hat Enterprise Linux (RHEL)</li>
<li>Ubuntu LTS (Canonical)</li>
</ul><h3 class="jobSectionHeader">Automation &amp; DevOps</h3>
<ul><li>CI/CD Pipeline Design &amp; Implementation</li>
<li>Infrastructure Automation</li>
<li>Platform Lifecycle Management</li>
<li>Configuration Management &amp; Orchestration</li>
</ul><h2 class="jobSectionHeader">Key Responsibilities</h2>
<ul><li>Design, deploy, and operate large-scale HPC and AI infrastructure environments from bare metal through workload orchestration.</li>
<li>Architect and manage NVIDIA GPU platforms, including BCM, AI Enterprise, GPU Operator, and AI service enablement.</li>
<li>Configure, optimize, and maintain Slurm scheduling environments for high-throughput and GPU-intensive workloads.</li>
<li>Design and operate highly available Kubernetes clusters supporting AI/ML, analytics, and containerized workloads.</li>
<li>Enable and support NVIDIA NIM services and AI Blueprint deployments for enterprise AI initiatives.</li>
<li>Administer and optimize RHEL and Ubuntu environments, ensuring stability, security, and performance.</li>
<li>Develop and maintain infrastructure automation frameworks and CI/CD pipelines for platform and application deployment.</li>
<li>Optimize performance across compute, GPU, storage, networking, and cluster resources.</li>
<li>Implement monitoring, observability, alerting, capacity planning, and operational best practices.</li>
<li>Enforce security, patch management, access controls, and compliance standards across the infrastructure stack.</li>
<li>Lead troubleshooting, root cause analysis, and resolution of complex infrastructure and platform issues.</li>
</ul><h2 class="jobSectionHeader">Candidate Profile</h2>
<ul><li>10+ years of hands-on experience in HPC, Linux infrastructure, and enterprise platform engineering.</li>
<li>Proven track record of building and operating production-scale HPC, GPU, or AI infrastructure environments.</li>
<li>Deep expertise in Kubernetes, Slurm, Linux administration, and NVIDIA AI technologies.</li>
<li>Strong understanding of distributed systems, workload scheduling, cluster management, and performance optimization.</li>
<li>Experience supporting AI/ML, data science, and high-performance computing workloads at scale.</li>
<li>Strong analytical, troubleshooting, and problem-solving skills.</li>
<li>Ability to work across infrastructure, platform, automation, and AI enablement domains.</li>
<li>Demonstrated ownership mindset with a history of delivering reliable, scalable, and high-performing solutions.</li></ul></div></div>

Senior Infrastructure / HPC

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