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Home/Jobs/Lead Data Scientist
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Envision Employment Solutions

Lead Data Scientist

🇦🇪 Dubai, UAE🏢 On-site
AIMachine LearningLLMsNLPData GovernancePythonCloud Computing
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Envision Employment Solutions is currently hiring a Lead Data Scientist for one of our partners, a global leader in IT Services and IT Consulting.

Job Summary:

We are seeking a visionary AI leader to drive enterprise-scale AI strategy, architecture, and delivery. This role requires deep expertise in large language models (LLMs), AI governance, and production-grade ML platforms, combined with strong leadership and executive communication capabilities.

The ideal candidate has extensive experience building and scaling enterprise AI ecosystems and leading multidisciplinary teams across complex environments.

Responsibilities:

Strategic AI Leadership

• Define and drive AI roadmaps aligned with corporate strategy
• Oversee the full model lifecycle from research and experimentation to production deployment
• Ensure measurable ROI and business impact from AI initiativesLLM & NLP Architecture (Enterprise Level)

• Design LLM ecosystems including RAG pipelines, orchestration layers, and fine-tuning strategies
• Lead domain-specific model fine-tuning and pretraining using proprietary datasets
• Integrate platforms such as Azure OpenAI, AWS Bedrock, Anthropic Claude, and Google Vertex AI
• Define governance, compliance, and security frameworks for LLM deployments
• Establish evaluation standards for hallucination rate, factual accuracy, bias, and toxicityInfrastructure & Governance

• Own data governance policies and feature store strategy
• Lead model observability, monitoring, and drift management frameworks
• Partner with DevOps and Security to ensure scalability, resilience, and complianceTeam & Stakeholder Leadership

• Build and lead multidisciplinary AI teams including Data Scientists, ML Engineers, and Data Engineers
• Mentor senior scientists and define research best practices
• Communicate directly with executive leadership and non-technical stakeholders
• Evaluate AI vendors and technology partnershipsRequirements

Qualifications:

• Master’s or PhD in AI, Machine Learning, Computer Engineering, or Applied Math or a related field
• Minimum 7 years of overall professional experience
• At least 2+ years in AI/ML leadership roles
• Proven ability to build and scale enterprise-level AI/LLM platforms.Leadership Competencies

• Visionary mindset driving innovation across business units.
• Excellent executive communication and influence skills.
• Focused on measurable ROI, scalability, and ethical AI.
• Mentors senior scientists, defining best practices and research direction.Benefits

Benefits & Work Setup

• Basic salary
• Family Medical Insurance
• Round-trip family flight tickets once per year
• Visa coverage
• Location: Dubai
• Work Model: Hybrid – 2 days in the office and 3 days remote. If assigned to a project, you may be required to work from the client’s premises on a daily basis, depending on the project requirements.
• Working Hours: 9 AM to 6 PM
• Days Off: Saturdays and Sundays

Requirements

  • •Master’s or PhD in AI, Machine Learning, Computer Engineering, or Applied Math
  • •Minimum 7 years of overall professional experience
  • •At least 2+ years in AI/ML leadership roles
  • •Proven ability to build and scale enterprise-level AI/LLM platforms
  • •Visionary mindset driving innovation
  • •Excellent executive communication and influence skills
  • •Focused on measurable ROI, scalability, and ethical AI
  • •Mentors senior scientists, defining best practices and research direction

Nice to Have

  • •Own data governance policies and feature store strategy
  • •Lead model observability, monitoring, and drift management
  • •Partner with DevOps and Security for scalability and compliance
  • •Build and lead multidisciplinary AI teams
  • •Communicate directly with executive leadership
  • •Evaluate AI vendors and technology partnerships

Responsibilities

  • •Define and drive AI roadmaps aligned with corporate strategy
  • •Oversee the full model lifecycle from research to production deployment
  • •Ensure measurable ROI and business impact from AI initiatives
  • •Design LLM ecosystems including RAG pipelines, orchestration, and fine-tuning
  • •Lead domain-specific model fine-tuning and pretraining
  • •Integrate platforms (Azure OpenAI, AWS Bedrock, Claude, Vertex AI)
  • •Define governance, compliance, and security frameworks for LLMs
  • •Establish evaluation standards for hallucination, accuracy, bias, and toxicity

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