Data Scientist

Data Researcher / Data Scientist (Multiple Levels)

Location: Middle East (Relocation Provided)**

Compensation: Highly competitive, fully guaranteed package

About the Role

We're building a high-calibre team to explore, structure, and model large, messy, unconventional datasets. The work is research-driven, engineering-heavy, and mostly greenfield. We're hiring across levels, from exceptional early-career talent to experienced researchers and engineers, to help design the data and ML foundations of a long-term technical initiative.

What You'll Do

• Work with high-volume, multimodal, unstructured data
• Build ML models, research pipelines, and experimental workflows
• Design data systems that support rigorous, repeatable experimentation
• Investigate model behaviour, signal quality, and data structure
• Translate research ideas into scalable components

Data Researcher

• Explore data, design experiments, build early ML prototypes
• Senior levels lead research direction and methodology

Data Scientist / ML Engineer

• Build pipelines, ingestion workflows, and model-ready datasets
• Senior levels architect large-scale systems and guide platform strategy

Who Thrives Here

• Strong Python and ML fundamentals
• Experience with large or unstructured datasets
• Comfort with ambiguity, complexity, and open-ended research
• Ability to think in systems and reason scientifically

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  Get Hired
• Clear evidence of exceptional ability (research, competitions, open-source, or standout projects)

Not a Fit If Your Background Is Mainly

BI/reporting, KPI dashboards, clean dataset analytics, survey programming, ETL operations, finance-first analysis, LLM prompting without ML depth, coursework-only ML, or spreadsheet-heavy work

What We Offer

• Guaranteed annual compensation
• Full relocation and family support
• Healthcare, education, travel benefits
• Significant compute, tooling, and data access
• A team of strong peers and space to build from first principles

How to Apply

• Please send your CV and a brief summary of relevant experience

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