
SAP MENA
Data Science Expert
- Permanent
- Dubai, United Arab Emirates
- Experience 5 - 10 yrs
Job expiry date: 05/06/2026
Job overview
Date posted
21/04/2026
Location
Dubai, United Arab Emirates
Salary
AED 20,000 - 30,000 per month
Compensation
Job description
The Data Science Expert role within SAP Software-Design and Development in Dubai, United Arab Emirates focuses on transforming data into business decisions by identifying high-value business problems, framing analytical approaches, and delivering models and insights that improve customer outcomes and product performance. The role spans exploratory analysis, statistical modeling, experimentation, forecasting, segmentation, anomaly detection, causal analysis, and machine learning while collaborating closely with product, engineering, sales, operations, and finance stakeholders. The position requires defining success metrics, quantifying business impact, translating findings into actionable business recommendations, and influencing roadmap decisions using evidence-based insights. The role also contributes to AI-driven analytics using NLP, embeddings, and LLM-assisted workflows for summarization, classification, knowledge extraction, and decision support. The Data Science Expert leverages Python and SQL for data extraction, statistical analysis, feature engineering, model development, and analytical automation while applying hypothesis testing, experiment design, A/B testing, regression analysis, causal inference, and uncertainty interpretation. Responsibilities include implementing machine learning techniques such as classification, forecasting, clustering, recommendation systems, anomaly detection, and propensity modeling. The role requires building dashboards, visualizations, and executive-level data narratives, applying feature selection, model validation, error analysis, bias identification, and balancing trade-offs between accuracy and usability. The position also involves working with modern analytics platforms including notebooks, BI tools, cloud data warehouses, Apache Spark, and large-scale data processing environments while maintaining strong data quality, lineage, and governance standards. The role supports customers across Saudi Arabia and United Arab Emirates within an AI and industry expert team, delivering scalable, customer-centric AI solutions, influencing strategy, and enabling measurable business outcomes.
Required skills
Key responsibilities
- Identify high-value business problems and frame analytical approaches using exploratory analysis, statistical modeling, machine learning, and forecasting techniques to improve customer outcomes and product performance
- Conduct exploratory data analysis, segmentation, anomaly detection, causal analysis, and experimentation to generate insights and guide data-driven decision making
- Develop machine learning models including classification, clustering, recommendation systems, forecasting, and propensity modeling using Python, SQL, and advanced analytics techniques
- Define success metrics, quantify business impact, and translate model outputs into actionable recommendations for product, engineering, sales, operations, and finance stakeholders
- Build AI-driven analytics solutions using NLP, generative AI, embeddings, and LLM-assisted workflows including semantic search, summarization, classification, and knowledge extraction
- Create dashboards, visualizations, and executive-level data narratives using BI tools and analytics platforms to communicate insights effectively
- Implement feature engineering, feature selection, model validation, error analysis, and bias detection while balancing accuracy, performance, and usability
- Ensure data quality, governance, lineage, and compliance standards while working with large-scale data processing environments, cloud data warehouses, and Apache Spark
Experience & skills
- Possess minimum 6+ years of data science experience with strong analytical and modeling capabilities
- Demonstrate strong command of Python and SQL for data extraction, statistical analysis, feature engineering, and model development
- Demonstrate deep understanding of statistics and probability including hypothesis testing, experiment design, A/B testing, regression, and causal analysis
- Demonstrate hands-on experience with machine learning techniques including classification, forecasting, clustering, recommendation systems, anomaly detection, and propensity modeling
- Demonstrate expertise in AI technologies including NLP, generative AI, embeddings, and LLM-assisted analytics workflows
- Demonstrate experience working with modern analytics platforms including notebooks, BI tools, cloud data warehouses, and Apache Spark
- Demonstrate strong understanding of data governance, data quality, lineage, and compliance best practices
- Demonstrate ability to collaborate cross-functionally, influence business decisions, and deliver measurable business outcomes through data science solutions