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Head of Data & AI

Talent Seed
Riyadh, KSA
Full Time
Director
Yesterday
Machine LearningForecastingPythonData PipelinesStatistical ModelingRegression
Free

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Machine LearningForecastingPython
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About the Client

  • The client is building an AI first operating system for a critical, real world industry, connecting multiple stakeholders into a single intelligent platform.
  • The business is already operating at scale with thousands of active users and live enterprise deployments across multiple markets.

The Opportunity

  • This is a senior, hands on AI leadership role with a clear mandate: improve core machine learning systems, build intelligent decision making AI, and drive measurable operational efficiency.

What You’ll Be Responsible For

  • Owning and evolving the forecasting and optimisation engine.
  • Improving machine learning model accuracy across demand and inventory use cases.
  • Designing and deploying agentic AI systems that reduce manual intervention and inefficiencies.
  • Solving complex challenges such as low frequency / sparse data forecasting.
  • Building and scaling production grade ML systems and pipelines.
  • Working with large, multi source datasets across operational systems.
  • Driving AI adoption across multiple business functions.
  • Leading a lean, high impact data science team, while staying hands on.

Experience Required

  • 7–12+ years in Data Science / Machine Learning (strong hands on expertise).
  • Proven experience building and improving forecasting models.
  • Strong experience with statistical and ML approaches (e.g., regression, tree based models).
  • Ability to choose and apply the right model to complex, real world problems.
  • Experience deploying ML systems into production environments.
  • Strong coding skills (Python, ML frameworks, data pipelines).
  • Experience leading teams while remaining deeply hands on.

Nice to Have

  • Experience with agentic AI systems or decision automation.
  • Exposure to optimisation, reinforcement learning, or advanced ML approaches.
  • Background in operations heavy environments (e.g., logistics, marketplaces, etc.).

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