Opportunity Information
1
Industry/ Manufacturing (National)
Managerial/ Experienced Professional
Regular/ Full Time
On Site
Karachi
The Role
National Foods Limited is hiring a Manager Data and AI (Corporate Office, Karachi). Lead the Data & AI function within DDT, enabling the organization to create measurable value from trusted data, advanced analytics, and AI (including GenAI) for strategic decision-making and operational excellence. Drive the roadmap, delivery, and governance of analytics and AI platforms, semantic models, and data/ AI products, ensuring alignment with DDT’s federated structure, security and compliance requirements, and business objectives.
•Support the Head of ERP & Application in defining and executing the enterprise Data & AI strategy and ensuring alignment with business priorities •Own and maintain the Data & AI roadmap (use-cases, platforms, governance), including prioritization, value tracking, and delivery cadence across the federated model •Partner with business leaders to identify, assess, and deliver high-impact analytics, AI/ ML, and GenAI use-cases; translate requirements into scalable data/ AI products •Lead solution design for analytics and AI products, including data pipelines, feature/ semantic layers, model serving patterns, and integration with business workflows •Manage the operational development of semantic layers and curated datasets, ensuring data is validated, structured, and business-ready with clear KPI definitions •Work with data engineering teams to ensure timely data ingestion, quality checks, observability, and pipeline reliability •Develop and govern BI products (dashboards, reports, self-service datasets) for Sales, Finance, SCM, Marketing, Export, HR, and Manufacturing; drive adoption and consistent UX standards •Build, deploy, and operationalize ML models (e.g., forecasting, segmentation, optimization, risk) and establish MLOps practices (CI/ CD, model registry, monitoring, drift/ quality checks, versioning) •Lead AI experimentation and delivery (e.g., copilots, RAG/ search, summarization, knowledge assistants) with strong focus on security, privacy, and evaluation (quality, grounding, toxicity, bias) •Define and enforce Responsible AI and AI governance controls (model risk, approvals, documentation, explainability, auditability), in partnership with Cybersecurity, Legal, and Compliance •Ensure adherence to data governance, quality standards, naming conventions, metadata/ lineage practices, and KPI frameworks •Establish standard ways of working: intake & discovery, PoC-to-production criteria, product documentation, and post-deployment value measurement •Provide hands-on guidance and coaching across tools and practices (Power BI, SQL, Python, DAX, ML frameworks, prompt engineering fundamentals) to uplift capability and delivery quality •Drive adoption via training materials, workshops, enablement sessions, and support for day-to-day analytics and AI queries •Engage with vendors and implementation partners for analytics/ AI tools, cloud services, model platforms, and platform upgrades; manage licenses, subscriptions, and platform administration tasks •Ensure compliance with cybersecurity, privacy, and audit requirements for data access, reporting layers, models, and AI applications •Track product adoption and business impact (usage, value realized, SLA/ quality KPIs) and prepare performance reports for leadership
Applicants General Eligibility & Requirements
5+ years
Education, Experience and Skills Requirements
- Bachelor 16 Years: Computer Science, Data Science, Statistics, Mathematics, Engineering
- Masters: Data Science
5+ years in data, analytics, BI, and/ or AI/ ML roles with proven experience leading teams and delivering data/ AI products end-to-end Preferred: •Hands-on experience with cloud data & AI platforms (Azure/ AWS/ GCP), modern data warehousing/ lakehouse patterns, and BI ecosystems (Power BI/ Tableau/ Qlik) •Practical experience building and operationalizing ML solutions, including MLOps (monitoring, drift, CI/ CD, model registry) and model risk/ controls •Exposure to GenAI use-cases (e.g., copilots, RAG, summarization) and understanding of Responsible AI, privacy, and security considerations
Preferred: Azure/ AWS/ GCP, Power BI, MLOps, Data Warehousing, GenAI
•Certifications in analytics/ cloud/ AI preferred (e.g., Azure Data Scientist/ AI Engineer, AWS ML Specialty, Google Professional ML Engineer, Power BI)