In this role, you'll turn data into decisions by identifying high-value business problems, framing them analytically, and delivering models and insights that improve customer outcomes and product performance. You’ll work across exploratory analysis, statistical modeling, experimentation, forecasting, segmentation, anomaly detection, causal analysis, and machine learning, while partnering closely with product, engineering, sales, operations, or finance stakeholders. Your work will not stop at model accuracy: you'll define success metrics, quantify impact, translate findings into business actions, and help teams prioritize based on value, risk, and feasibility. You’ll also contribute to AI-driven analytics using NLP, embeddings, and LLM-assisted workflows for summarization, classification, knowledge extraction, and decision support. The role requires someone who can connect business context with rigorous analysis, explain trade-offs clearly, and influence roadmap decisions with evidence.
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Requirements
- Strong command of Python and SQL for data extraction, statistical analysis, feature engineering, model development, and analytical automation
- Deep understanding of statistics and probability, including hypothesis testing, experiment design, A/B testing, regression, causal thinking, and interpreting uncertainty
- Hands-on experience with a range of machine learning techniques, such as classification, forecasting, clustering, recommendation systems, anomaly detection, and propensity modeling
- Skills in framing business problems into measurable analytical questions, defining success metrics, and connecting model outputs to commercial or operational decisions
- Ability to build clear data narratives through dashboards, visualizations, presentations, and concise executive communication
- Practical expertise in feature selection, model validation, error analysis, bias identification, and balancing trade-offs between accuracy and usability
- Exposure to modern AI approaches, including NLP, generative AI, and LLM-assisted analytics (e.g., semantic search, text classification, summarization, prompt-based analysis)
- Experience with modern analytics and data platforms, such as notebooks, BI tools, cloud data warehouses, Spark, and large-scale data processing environments
- Strong understanding of data quality, lineage, governance, and the discipline required to produce trustworthy and reusable analyses
About You
- 6+ years of data science experience
- Curiosity and a structured approach to problem-solving, with the ability to break down complex challenges into clear, actionable steps
- Strong collaborator who enjoys working cross-functionally and influencing decisions through data
- Motivated by driving real-world impact, ensuring analyses and models lead to measurable business outcomes
- Continuously seeking to learn and stay current with evolving data science and AI trends
Work Conditions
- Expected Travel: 0 - 10%
- Career Status: Professional
- Employment Type: Regular Full Time
- Additional Locations: #LI-Hybrid
Location
Kingdom of Saudi Arabia / United Arab Emirates
