ai governance lead

Pakistan Digital Authority

<div>
 
 The Pakistan Digital Authority is Pakistan's apex statutory body for national digital transformation, established under the Digital Nation Pakistan Act 2025. PDA is responsible for the country's Digital Public Infrastructure (DPI), AI and data governance frameworks, national digital standards, and the Digital Nation Masterplan &mdash; a cross-government programme covering all provinces, the whole of government, and 240 million citizens.
 
 
 
 
 
 This is not a typical government role. PDA operates with the mandate of a regulator, the ambition of a national transformation programme, and the urgency of a startup.
 
 
 
 
 
 
 The Role
 
 
 
 
 
 
 The Chief AI Officer is a founding executive appointment at PDA and the senior-most AI leadership role in Pakistan's public sector.
 
 
 
 
 
 You will carry two distinct but deeply connected mandates: AI supervision &mdash; building the regulatory, governance, and oversight architecture that governs how AI is developed and deployed across Pakistan; and AI use-case strategy &mdash; identifying, prioritising, and driving the AI applications that will transform government services and public outcomes at scale.
 
 
 
 
 
 You will report directly to the Chairperson and work alongside the Chief Data Officer and be part of PDA's integrated technology governance team.
 
 
 
 
 
 
 What You Will Lead
 
 
 
 
 
 
 AI Governance &amp; Supervision
 
 
 &rtrif; Lead the development of Pakistan's National AI Governance Framework &mdash; covering AI risk classification, algorithmic accountability, transparency requirements, and prohibited use definitions
 
 
 
 
 
 &rtrif; Own PDA's AI regulatory instruments under the Digital Nation Pakistan Act &mdash; including government AI use policies, AI audit frameworks, and conformity assessment protocols for high-risk AI systems
 
 
 
 
 
 &rtrif; Help establish the National AI Advisory Council &mdash; convening government, academia, civil society, and industry to inform national AI policy
 
 
 
 
 
 &rtrif; Develop Pakistan's position on sovereign AI infrastructure &mdash; national compute, foundational models, and AI supply chain resilience
 
 
 
 
 
 
 AI Strategy &amp; Use-Cases
 
 
 
 &rtrif; Build and own PDA's government AI use-case portfolio &mdash; identifying highest-impact applications across health, justice, education, taxation, social protection, and public safety
 
 
 
 
 
 &rtrif; Lead the strategy and oversight of PDA's AI solutions suite
 
 
 
 
 
 &rtrif; Design the AI maturity assessment framework for federal ministries and lead national AI readiness diagnostics
 
 
 
 
 
 &rtrif; Drive Pakistan's AI talent and capability strategy in partnership with higher education institutions and the technology industry
 
 
 
 
 
 &rtrif; Build and lead PDA's AI Division &mdash; hiring AI policy specialists, applied AI engineers, and research capacity
 
 
 
 
 
 
 What We Are Looking For
 
 
 
 
 
 
 Essential
 
 
 ✔ 15+ years of progressive experience spanning AI/ML, technology strategy, or technology policy &mdash; with significant leadership tenure
 
 
 ✔ Demonstrated command of AI governance principles: risk-based classification, algorithmic accountability, explainability, fairness, and AI safety
 
 
 ✔ Track record of leading AI strategy at organisational or national scale &mdash; governance and policy architecture, not just AI delivery
 
 
 ✔ Ability to operate fluently across technical and policy registers &mdash; credible with engineers and with ministers
 
 
 ✔ Experience building and leading high-performing cross-functional teams in complex institutional environments
 
 
 
 
 
 Highly Valued
 
 
 ✦ Experience in a national AI authority, government AI body, or equivalent institution
 
 
 ✦ Deep familiarity with international AI governance frameworks: EU AI Act, OECD AI Principles, NIST AI RMF, UNESCO Recommendation on AI Ethics
 
 
 ✦ Hands-on experience with large language models, Generative AI deployment, and the governance challenges they create in public sector contexts
 
 
 ✦ Exposure to sovereign AI infrastructure &mdash; national compute strategy, open-source foundation models, AI procurement policy ✦ Understanding of AI's intersection with data governance, digital identity, and digital public infrastructure
 
 
 
 
 
 
 Why PDA
 
 
 
 &rarr; Shape the AI governance architecture of a nation of 240 million people &mdash; one of the highest-impact AI leadership roles in the developing world &rarr; Direct reporting line to the Chairperson &amp; CEO; seat at PDA's executive leadership table &rarr; Influence Pakistan's AI legislation, international AI commitments, and the sovereign AI infrastructure agenda
 
 
 &rarr; Competitive compensation benchmarked to Pakistan's senior public sector reform appointments and international GovTech norms
 
</div>

Chief AI Officer

Etisalat

<div><div>AI Engineering &amp; Innovation Manager.Customer and Partner Management - (260000V2)</div><div>
Description<div></div> 
Job Purpose
To lead the AI Engineering &amp; Innovation function, with primary focus on AI Development, AI/ML Engineering, Generative AI, and Agentic AI solutions, supported by strong background in platform engineering and full-stack architecture. Responsible for delivering cutting-edge AI solutions, including AI Agents, Agentic Automation, OCR, Chatbots, Conversational AI, Speech-to-Text, Text-to-Speech, Voicebots, and local LLM deployments&mdash;while ensuring solutions are scalable, secure, production-ready, and aligned with enterprise architecture standards. The role drives end-to-end innovation, from lean experimentation and proof-of-concepts to enterprise-scale deployment, ensuring AI solutions are aligned with business strategy, customer experience goals, and market-leading practices.

Report To Position Name
Leadership &amp; Strategy Lead and manage a team of AI Development Engineers, AI/ML Engineers, AI Agent Engineers, and AI Support Engineers. Define AI Engineering and Innovation roadmap aligned with corporate digital transformation strategy. Evaluate emerging AI technologies (LLMs, local LLMs, RAG, AI agents, agent frameworks, vector databases, orchestration layers, and autonomous workflows) and introduce new capabilities. Drive adoption of AI to enhance customer care, CVM, digital channels, enterprise services, and internal efficiency. Establish standards for reusable AI components, agent design, governance, and scalable enterprise AI adoption. AI Development Oversee design and development of AI/ML models, Generative AI applications, reusable AI agents, and agentic workflows for OCR, NLP, Chatbots, Conversational AI, and automation use cases. Guide teams in model training, fine-tuning, prompt engineering, evaluation, deployment, and agent orchestration. Lead deployment and optimization of local / on-prem LLM models, including model serving, inference optimization, GPU utilization, and continuous tuning. Drive integration of speech-to-text, text-to-speech, voicebot, and voice persona capabilities into customer-facing and enterprise applications. Ensure compliance with data governance, model governance, ethical AI use, and responsible AI principles. Design modular, reusable, and scalable AI agents with governance controls and shared services. AI Platforms Engineering Provide architectural oversight leveraging strong platform engineering and full-stack development background(Java, Spring Boot, Node.js, Angular). Ensure robust solution architecture using microservices, containerization, Docker, Kubernetes / OpenShift, Amazon EKS orchestration, APIs, and CI/CD pipelines. Lead production deployment and go-live readiness with full focus on security controls, vulnerability management, secure coding practices, and infrastructure hardening. Integrate AI solutions with enterprise platforms, core systems, vector stores, tool layers, and backend services. Oversee performance, scalability, resilience, and production readiness of AI applications and services. Innovation, Proof-of-Concepts &amp; Productization Lead innovation lifecycle: identify opportunities, run lean experiments, build PoCs, validate impact, and scale successful use cases to production. Collaborate with business units to co-create AI-powered products, agentic workflows, and automation services. Drive rapid experimentation cycles with measurable business impact and customer value. Ensure accelerated time-to-value and time-to-market for AI solutions while maintaining quality and security. Operations &amp; AIOps Ensure operational readiness of deployed AI applications through AIOps, MLOps, and LLMOps monitoring and automation. Oversee incident resolution, model monitoring, change management, and continuous improvement. Maintain SLAs and service reliability for critical AI-enabled business applications. Ensure continuous security patching, vulnerability remediation, and model/runtime lifecycle management.<div> 
</div></div><div>
Qualifications<div></div> 
QUALIFICATIONS_ESSENTIAL
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Engineering, AI, or related field 
QUALIFICATIONS_DESIRABLE
Innovation Drive adoption of next-gen AI architectures (Agentic orchestration, vector databases, RAG pipelines). Lead experimentation with new AI platforms and integration models. Skills &amp; Abilities Strong leadership, people management, and cross-functional collaboration. Excellent communication, presentation, and stakeholder engagement skills. Ability to manage multiple parallel projects and deliver under pressure. 

EXPERIENCE_ESSENTIAL
8+ years of experience in AI/ML engineering and software development. At least 3&ndash;5 years in a leadership/managerial role overseeing AI development teams 
EXPERIENCE_DESIRABLE
Strong knowledge of AI/ML technologies (Machine Learning, NLP, Generative AI, Agentic AI, Conversational AI, OCR, autonomous workflows). Proven experience in AI development, reusable agent design, and scalable AI solution engineering. Strong hands-on familiarity with cloud platforms and their AI portfolios, including AWS (Bedrock, SageMaker), Microsoft Azure AI services, and Google Cloud Vertex AI / GenAI services. Solid background in platform engineering, full-stack architecture, microservices, containerization, APIs, and orchestration platforms such as Docker, OpenShift, and EKS. Proven go-live deployment experience with strong focus on security, vulnerability management, and production hardening. Experience in deploying and managing local / on-prem LLM models and inference environments. Familiarity with speech technologies (speech-to-text, text-to-speech, voicebots, voice persona solutions). Deep understanding of cloud, DevOps, MLOps, LLMOps, governance, and observability tools. Strong knowledge of lean experimentation methodologies with impact-driven delivery. Knowledge of telecom, customer care, CVM, sales, and enterprise domains is a plus. 

CERTIFICATIONS_ESSENTIAL
N/A<div> 
</div></div><div>
Job: Manager</div><div>
Organization: Etisalat-Misr</div><div>
Job Posting: 06/May/2026, 6:51:31 AM</div></div>

AI Engineering & Innovation Manager.Customer and Partner Management

Abdulla Al Ghurair Foundation

Lead the definition, governance, and evolution of AGF&rsquo;s enterprise digital architecture, ensuring that systems, platforms, data environments,integrations, and AI capabilities support the Foundation&rsquo;s mission, programs, beneficiary lifecycle, grants ecosystem, and partner engagements.Establish and maintain a scalable, secure, and integrated technology foundation that enables operational excellence, regulatory compliance(including PDP and financial compliance), and data-driven decision-making across the organization.Strategic<ul><li>Define and maintain AGF&rsquo;s enterprise architecture framework across CRM, ERP (Microsoft Dynamics FinOps), data platforms, integrations, and AI systems.</li></ul><ul><li>Design a unified digital ecosystem supporting beneficiary lifecycle management, grants lifecycle workflows, partner engagement, and internal operational coordination.</li></ul><ul><li>Drive alignment between business strategy and technical capabilities, ensuring platforms are scalable, interoperable, and future-ready.</li></ul><ul><li>Lead the AI architecture roadmap and ensure responsible, ethical, and secure implementation of AI-driven capabilities.</li></ul><ul><li>Guide technology investment decisions, platform selection, and vendor architecture alignment.</li></ul>Governance Responsibilities<ul><li>Own enterprise architecture governance, technical standards, and system design principles across AGF.</li></ul><ul><li>Define integration standards, API governance, and platform interoperability frameworks.</li></ul><ul><li>Ensure that all system developments align with AGF&rsquo;s digital transformation roadmap and long-term institutional needs.</li></ul><ul><li>Provide technical oversight for system changes, upgrades, and digital initiatives across departments.</li></ul>Compliance Responsibilities<ul><li>Embed privacy-by-design and compliance-by-design principles into system architecture.</li></ul><ul><li>Ensure alignment of systems and data structures with UAE PDP Law requirements and data protection best practices.</li></ul><ul><li>Support e-invoicing readiness by ensuring ERP architecture can support regulatory compliance and traceability.</li></ul><ul><li>Collaborate with Legal and Cybersecurity to ensure secure, compliant handling of beneficiary, partner, and grant-related data.</li></ul><ul><li>Ensure AI systems comply with ethical, governance, and risk management frameworks.</li></ul>Data Accountability<ul><li>Own and define enterprise data architecture, including master data models, integration layers, and governance structures.</li></ul><ul><li>Ensure data flows across CRM, ERP, program platforms, and reporting tools are consistent, traceable, and reliable.</li></ul><ul><li>Support the creation of a single source of truth for beneficiaries, partners, grants, and operational data.</li></ul><ul><li>Work closely with MERL to ensure data models support impact measurement, analytics, and performance tracking.</li></ul>Systems Accountability<ul><li>Oversee architecture alignment across core platforms including CRM, ERP (Dynamics FinOps), analytics platforms, AI tools, and integration layers.</li></ul><ul><li>Ensure long-term sustainability, scalability, and performance optimization of AGF&rsquo;s digital ecosystem.</li></ul><ul><li>Guide system integration strategies to prevent fragmentation, duplication, and data silos.</li></ul><ul><li>Ensure systems support operational workflows across programs, grants, finance, HR, and partnerships.</li></ul>Job Type: Full-timeWork Location: Remote

Head of Digital Architecture & AI Systems

Tiro International

<div>
 
 Our client &ndash; operating in the
 
 FMCG sector
 
 is looking for a Chief Technology Officer.
 
 
 
 
 
 
 The role will be
 
 physically located in Kuala Lumpur &ndash; Malaysia.
 
 
 
 
 
 
 
 
 Job Summary:
 
 
 
 
 
 Responsible for architecting and delivering the Group&rsquo;s end-to-end digital evolution across global trading, refinery, manufacturing, supply chain, warehousing, and distribution operations.
 
 
 
 
 
 
 This role is created to reposition the Group from a traditional integrated commodity and FMCG player into a technology-empowered, data-intelligent and globally synchronized enterprise.
 
 
 
 
 
 
 
 
 Primary responsibilities include:
 
 
 
 
 Enterprise Digital Transformation Leadership
 
 
 <ul>
 <li>
 Design and execute a bold 5-year Digital &amp; Technology Transformation Blueprint.
 </li>
 <li>
 Lead the enterprise-wide modernization of legacy systems into integrated, scalable digital platforms while progressively embedding AI capabilities into core daily operations.
 </li>
 <li>
 Re-architect technology to support global expansion and potential new market expansion using new cloud-based technology with a global control tower dashboard for senior leadership based in HQ.
 </li>
 <li>
 Drive digitization across trading, manufacturing, and logistics operations.
 </li>
 <li>
 Transform IT from a support function into a strategic growth engine.
 </li>
 </ul>
 
 
 
 
 
 Global ERP &amp; Systems Harmonization
 
 
 <ul>
 <li>
 Lead proven, large-scale ERP deployments across multi-country operations.
 </li>
 <li>
 Standardize global business processes across:
 </li>
 <li>
 Trading &amp; commodity risk management
 </li>
 <li>
 Manufacturing &amp; production planning
 </li>
 <li>
 Inventory &amp; warehouse management
 </li>
 <li>
 Supply chain &amp; distribution
 </li>
 <li>
 Finance &amp; consolidation
 </li>
 <li>
 Distribution system and sales force automation for FMCG
 </li>
 <li>
 Build a single source of truth data platform across the Group.
 </li>
 <li>
 Implement global data governance and reporting architecture.
 </li>
 <li>
 Lead development of business dashboards for monitoring and tracking financial and operational KPIs.
 </li>
 <li>
 Reduce system fragmentation and manual reconciliation risks, replacing them with AI workflow orchestration solutions.
 </li>
 </ul>
 
 
 
 
 
 Technology-Enabled Trading &amp; Risk Excellence
 
 
 <ul>
 <li>
 Digitally enhance commodity trading platforms with:
 </li>
 <li>
 Real-time analytics
 </li>
 <li>
 Risk management dashboards
 </li>
 <li>
 Exposure visibility
 </li>
 <li>
 Margin intelligence tools
 </li>
 <li>
 Strengthen controls and governance to mitigate trading and compliance risks.
 </li>
 <li>
 Integrate finance, trading and supply chain data for unified visibility.
 </li>
 </ul>
 
 
 
 
 
 AI, Data &amp; Advanced Analytics Strategy
 
 
 <ul>
 <li>
 Establish a Group-wide enterprise data architecture.
 </li>
 <li>
 Build advanced analytics capabilities across:
 </li>
 <li>
 Demand forecasting
 </li>
 <li>
 Procurement optimization
 </li>
 <li>
 Production efficiency
 </li>
 <li>
 Commodity pricing insights
 </li>
 <li>
 Drive AI adoption responsibly and strategically.
 </li>
 <li>
 Elevate executive decision-making through real-time dashboards.
 </li>
 <li>
 Champion adoption of an AI-first mindset across all business units.
 </li>
 </ul>
 
 
 
 
 
 Strategic Budgeting
 
 
 <ul>
 <li>
 Own and optimize global technology CAPEX and OPEX budgets.
 </li>
 <li>
 Develop disciplined ROI-driven investment frameworks.
 </li>
 <li>
 Prioritize digital investments aligned with business growth.
 </li>
 <li>
 Lead vendor strategy, contract negotiation and platform rationalization.
 </li>
 <li>
 Ensure every technology initiative delivers measurable value.
 </li>
 </ul>
 
 
 
 
 
 Cybersecurity &amp; Enterprise Risk Governance
 
 
 <ul>
 <li>
 Build a resilient cybersecurity framework across global operations.
 </li>
 <li>
 Strengthen disaster recovery and business continuity planning.
 </li>
 <li>
 Protect trading, financial and operational data integrity.
 </li>
 <li>
 Implement global compliance and regulatory frameworks.
 </li>
 <li>
 Conduct regular risk maturity assessments and audits.
 </li>
 <li>
 Prepare and operationalize IT Delegation of Authority for enhanced governance.
 </li>
 </ul>
 
 
 
 
 
 Executive &amp; Board-Level Leadership
 
 
 <ul>
 <li>
 Serve as a strategic advisor to the Board on digital opportunities.
 </li>
 <li>
 Translate technology transformation into shareholder value.
 </li>
 <li>
 Partner with regional CEOs and senior leadership team.
 </li>
 <li>
 Influence digital culture across all geographies.
 </li>
 </ul>
 
 
 
 
 
 Global Team Building &amp; Organizational Design
 
 
 <ul>
 <li>
 Build a high-caliber, future-ready technology organization.
 </li>
 <li>
 Develop strong regional technology leadership bench strength.
 </li>
 <li>
 Introduce performance metrics aligned to business outcomes.
 </li>
 <li>
 Foster a culture of innovation, accountability and execution excellence.
 </li>
 <li>
 Attract global talent capable of operating in multi-country environments.
 </li>
 </ul>
 
 
 
 
 
 Role Requirements:
 
 
 <ul>
 <li>
 15&ndash;20+ years of progressive technology leadership experience, including at least 8&ndash;10 years in executive roles such as IT Director, CIO or CTO.
 </li>
 <li>
 Proven experience leading multi-country ERP implementations across trading, manufacturing, supply chain, warehousing, and distribution environments.
 </li>
 <li>
 Demonstrated success in enterprise-wide digital transformation.
 </li>
 <li>
 Experience in AI and data strategy deployment.
 </li>
 <li>
 Executive gravitas and Board-level influence.
 </li>
 <li>
 Proven ability to build and lead high-performing global teams.
 </li>
 <li>
 Experience operating in emerging markets and complex, multi-entity organizations is highly desirable.
 </li>
 <li>
 Relevant professional certifications in ERP platforms (e.g., SAP, Oracle, Microsoft Dynamics), enterprise architecture, cybersecurity governance, project management, and cloud technologies are strongly preferred.
 </li>
 <li>
 Executive education in digital strategy, Industry 4.0, or corporate governance would further strengthen the profile.
 </li>
 </ul>
 
 
 
 
 
 What's on offer:
 
 
 <ul>
 <li>
 Monthly Salary: USD 9,000 - 9,500/- p.m. (Basic+Housing+Transporatation)
 </li>
 <li>
 Education allowance for children
 </li>
 <li>
 Family medical insurance
 </li>
 <li>
 Family air-tickets
 </li>
 <li>
 Annual Performance Bonus
 </li>
 </ul>
</div>

Chief Technology Officer

Ejadah Management Consultancy

<div>
 
 
 Key Responsibilites:
 
 
 
 Lead the end-to-end
 
 AI delivery function
 
 , ensuring consistent, high-quality execution across multiple squads and business domains
 
 <ul>
 <li>
 Oversee the
 
 full lifecycle of AI initiatives
 
 , from use case identification and prioritization through to deployment, scaling, and continuous optimization
 </li>
 <li>
 Establish and institutionalize
 
 delivery governance frameworks
 
 , including clear operating models, performance cadence, and accountability structures
 </li>
 <li>
 Build and lead
 
 high-performing, cross-functional teams
 
 , including engineering, data science, and product, operating through layered leadership
 </li>
 <li>
 Define and implement
 
 scalable AI platform architectures
 
 , enabling reuse, interoperability, and efficient deployment across the enterprise
 </li>
 <li>
 Drive the adoption of
 
 enterprise-grade MLOps standards
 
 , including CI/CD pipelines, model versioning, automated testing, and controlled release processes
 </li>
 <li>
 Ensure robust
 
 AI lifecycle management and model governance
 
 , including monitoring, drift detection, retraining strategies, and incident management protocols
 </li>
 <li>
 Standardize delivery through
 
 platform-based approaches
 
 , including shared data pipelines, reusable components, and consistent model serving patterns
 </li>
 <li>
 Collaborate closely with business and technology leadership to ensure
 
 alignment between AI delivery and strategic priorities
 
 </li>
 <li>
 Define and track
 
 key performance indicators
 
 related to delivery efficiency, model performance, and business value realization
 </li>
 <li>
 Ensure adherence to
 
 responsible AI principles
 
 , including auditability, transparency, and regulatory alignment
 </li>
 </ul>
 
 
 
 
 
 Requirments:
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related discipline;
 
 advanced degree preferred
 
 </li>
 <li>
 Minimum of 10 years of experience in
 
 AI, machine learning, advanced analytics, or software engineering
 
 , with a strong record of delivering solutions in production environments
 </li>
 <li>
 Demonstrated success in leading
 
 large-scale AI delivery functions
 
 , including managing managers and cross-functional teams within complex organizations
 </li>
 <li>
 Deep expertise in
 
 MLOps and ML lifecycle management
 
 , including model versioning, CI/CD, monitoring, and continuous improvement practices
 </li>
 <li>
 Strong understanding of
 
 enterprise AI architectures
 
 , including data pipelines, feature stores, model serving, and hybrid cloud/on-premise environments
 </li>
 <li>
 Proven ability to design and scale
 
 platform-based AI capabilities
 
 , enabling reuse and consistency across multiple use cases
 </li>
 <li>
 Experience operating within structured environments requiring
 
 governance, controls, and auditability
 
 , preferably within regulated or large-scale industries
 </li>
 <li>
 Strong
 
 stakeholder management and communication capabilities
 
 , with the ability to engage senior leadership and translate business objectives into execution
 </li>
 <li>
 Demonstrated ability to balance
 
 strategic thinking with hands-on delivery oversight
 
 , ensuring both direction and execution excellence
 </li>
 </ul>
 
 
 
 
 
 
</div>

Ai Delivery Director

HUMAIN

<div>
 
 We are Hiring for Director, Strategic Sourcing - AI Solution &amp; AI Product
 
 
 
 🔹 Role Overview
 
 
 
 Lead sourcing strategy across managed services, software development, hosting, and AI-driven solutions. Own end-to-end category management while embedding AI into decision-making, supplier evaluation, and negotiations.
 
 
 
 🔹 Key Responsibilities
 
 
 
 &bull; Lead sourcing for managed services, software development, and hosting solutions
 
 
 &bull; Run AI-enabled RFX events and automate sourcing processes
 
 
 &bull; Develop advanced cost, TCO, and risk models
 
 
 &bull; Apply AI for supplier evaluation, bid analysis, and performance prediction
 
 
 &bull; Ensure compliance, governance, and performance monitoring through digital tools
 
 
 &bull; Drive innovation through supplier partnerships and agile sourcing practices
 
 
 &bull; Implement AI tools for automation, analytics, and sourcing optimization
 
 
 
 🔹 Qualifications
 
 
 
 &bull; Bachelor&rsquo;s degree in IT, Business, Computer Science, or related field (MBA preferred)
 
 
 &bull; MCIPS preferred
 
 
 &bull; Agile/Scrum certification is a plus
 
 
 
 🔹 Preferred Experience
 
 
 
 &bull; 7&ndash;10 years in sourcing managed services, software, hosting, or IT services
 
 
 &bull; Strong experience in AI-driven procurement and digital sourcing tools
 
 
 &bull; Proven track record in cost optimization and service delivery improvement
 
 
 
 🔹 Key Competencies
 
 
 
 &bull; Strategic Sourcing &ndash; Expert
 
 
 &bull; Contract &amp; Service Management &ndash; Expert
 
 
 &bull; Digital Solutions &amp; Infrastructure Knowledge &ndash; Advanced
 
 
 &bull; Market Intelligence &ndash; Advanced
 
 
 &bull; AI-Driven Procurement &ndash; Advanced
 
 
 
 🔹 Supporting Competencies
 
 
 
 &bull; Agile Methodology &ndash; Intermediate
 
 
 &bull; Stakeholder Management &amp; Collaboration &ndash; High
 
 
 &bull; Negotiation &amp; Influence &ndash; Expert
 
 
 &bull; Innovation Management &ndash; Advanced
 
 
 
 🔹 Technical Competencies
 
 
 
 &bull; AI for Sourcing Automation &ndash; Advanced
 
 
 &bull; Financial &amp; Cost Modeling &ndash; Advanced
 
 
 &bull; Hyper automation &amp; Digital Tools &ndash; Intermediate
 
 
 
 🔹 Expected Outcomes
 
 
 
 &bull; Deliver cost savings while maintaining high-quality service delivery
 
 
 &bull; Reduce sourcing cycle time through automation and AI
 
 
 &bull; Strengthen governance, compliance, and supplier performance
 
 
 &bull; Drive innovation through strategic partnerships and digital sourcing
 
</div>

Director, Strategic Sourcing – AI Solutions & Products (Procurement)

MA'ADEN

<div>Job Purpose
<ul><li><div>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.
</div></li><li><div>The role ensures analytics products are designed, validated, industrialized, governed, and adopted at scale, providing measurable value across mining, processing, operations, and enterprise functions.
</div></li><li><div>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 
</div></li></ul>Key Accountabilities:
1. Lead End-to-End Data Science Delivery
<ul><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><div>Ensuring data security and compliance with relevant regulations
</div></li><li><div>Drive experimentation, model versioning, automated retraining, and continuous improvement. 
</div></li></ul><div></div>2. Translate Business Needs into AI/Analytics Solutions
<ul><li><div>Establish frameworks and operating models that make data science accessible, scalable, and embedded within business and technical functions
</div></li><li><div>Engage BU/domain stakeholders to identify value creation opportunities and convert them into actionable analytics use cases.
</div></li><li><div>Build value hypotheses, KPIs, success criteria, and solution roadmaps in collaboration with Data &amp; AI leadership and business teams. 
</div></li></ul>3. Industrialize AI/ML Models (ML Ops &amp; Architecture)
<ul><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>Leverage machine learning, optimization, and computer vision as enabling tools for performance, reliability, and sustainability improvements 
<li>
</li></ul>4. Responsible AI, Quality &amp; Governance
<ul><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>Ensure transparency, explainability, and continuous model governance across production and enterprise environments 
<li>
</li></ul>5. Stakeholder Management &amp; Value Realization
<ul><li>Communicate insights, results, risks, and recommendations to decision-makers using compelling narratives and visualization.
</li>Track value realization, adoption metrics, and operational impact to ensure measurable benefit. 
<li>
</li></ul>Minimum Qualification, Experience and Core Competencies:
Minimum Qualifications:
<ul><li>Bachelor&rsquo;s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or related fields. 
</li></ul>Minimum Experience: 
 
 
<ul><li><div>Minimum Experience:
</div></li><li><div>8 &ndash; 10 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
</div></li><li><div>Proven ability to translate business problems into analytic approaches: define hypotheses, design analyses, and synthesize results into clear recommendations.
</div></li><li><div>Strong proficiency with modern ML frameworks and cloud platforms (TensorFlow, PyTorch , Azure, AWS) &ndash; Microsoft AI Factory
</div></li><li><div>Strong technical fluency with modern analytics stacks, data modeling, SQL, and experience partnering effectively with engineering teams. 
</div></li><li> 
Machine Learning &amp; Advanced Analytics
<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><li>Generative AI &amp; AI Agents
<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
 
 
Good to Have Capabilities
</li></ul></li><li>Data Engineering (IT + OT)
<ul><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></ul></li><li>MLOps / AgentOps
<ul><li>Experience in model deployment and lifecycle management , including:
<ul><li>Transition from model development to production and scale
</li><li>Monitoring, retraining, versioning, and drift management
</li></ul></li><li>Familiarity with automation and operationalization of ML/AI workloads
 
 
Preferred Experience &amp; Platforms
</li></ul></li><li>Cloud &amp; Analytics Platforms
<ul><li>Experience working with enterprise cloud platforms, preferably:
<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>
</li></ul></li></ul><div></div>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>

Principal Specialist, Data Science & Analytics

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