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Data Scientist, Senior-Level

Jobgether

Senior 🇬🇧 English
AI Architecture Cloud-native data platforms Mathematics Statistics Agentic AI systems Generative AI solutions LLM applications Data lifecycle management Data stewardship practices Machine Learning Data Quality Data Science

وصف الوظيفة

About the role

This senior-level Data Scientist position is based in Saudi Arabia and is listed on behalf of a partner company. The role focuses on shaping modern data ecosystems and delivering intelligent, agentic AI solutions that drive enterprise‑wide transformation.

Key responsibilities

  • Design, build and orchestrate agentic AI workflows, generative AI applications, LLM‑based solutions and autonomous systems.
  • Translate business objectives and user needs into structured product backlogs, user stories, technical requirements and execution roadmaps.
  • Own Data & AI initiatives from strategic definition through architecture, development, implementation and delivery.
  • Create modular, scalable and reusable Data and AI components for complex enterprise environments.
  • Apply rigorous data stewardship practices covering data quality, lifecycle management, privacy, governance, security and production readiness.
  • Collaborate closely with stakeholders, project managers, engineers and cross‑functional teams to bridge business and technical requirements.
  • Act as a trusted technical advisor, leading demonstrations, architecture discussions, workshops and high‑level stakeholder conversations.

Required profile

  • Minimum 60 months (5 years) of experience in data science, AI or related fields.
  • Strong analytical foundation combined with strategic thinking and technical leadership.
  • Proven ability to influence enterprise‑wide initiatives and drive innovation.
  • Excellent communication skills to translate complex concepts for both technical and business audiences.

Required skills

  • AI Architecture
  • Cloud‑native data platforms
  • Mathematics
  • Statistics
  • Agentic AI systems
  • Generative AI solutions
  • LLM applications
  • Data lifecycle management
  • Data stewardship practices
  • Machine Learning
  • Data Quality
  • Data Science

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