Mulham Al Akhras

I’m a Data Science & Analytics Leader with over 9 years of international experience helping organizations turn data into measurable business impact. My work spans the full analytics lifecycle - from exploratory data analysis and feature engineering to building, validating, and deploying machine learning models that solve real operational and customer challenges.

I’ve led initiatives to unify disconnected data systems, design scalable pipelines, and deliver interactive dashboards and KPIs that give leadership real-time visibility into performance. My approach combines technical depth with a clear understanding of business goals - translating models, metrics, and trends into actionable insights that drive strategy and decision-making.

Technically, I’m proficient in Python, SQL, Spark, and Databricks, with experience in model fine-tuning, cross-validation, and ensemble methods, and hands-on expertise across descriptive, diagnostic, predictive, and prescriptive analytics. I’m equally comfortable collaborating with engineers and product teams on architecture as I am presenting insights to executives and non-technical stakeholders.

At my core, I enjoy connecting data, technology, and business strategy - ensuring that every model, dashboard, or recommendation directly supports growth, efficiency, or improved user experience.