Data Science Lead Job in Dubai, United Arab Emirates

Role Overview
As the Data Science Lead within the Data and Analytics team at Al-Futtaim Group (AFG), you will play a crucial role in spearheading the development and implementation of data science initiatives across various functions. Reporting to the Head of Data Engineering & Operations, you will utilize AI and cloud technologies—primarily our Azure data platform—to enhance ROI through forecasting, predictive modeling, optimization, and large language models (LLMs). You will also assess new data sources from both SAP and non-SAP systems, transforming them into actionable datasets for insightful business analysis.

• Key Responsibilities
  Model Development: Design, document, and implement predictive models and machine learning algorithms that yield measurable ROI for stakeholders. Rapidly test and refine these models to align with emerging data and business needs.
• Project Leadership: Facilitate initial discussions on data potential and predictive insights to shape project scopes and deliverables, ensuring they align with strategic objectives.
• Data Architecture: Architect and manage scalable data pipelines to ensure efficient data ingestion and analysis, focusing on speed and data integrity.
• Advanced Technologies: Leverage cutting-edge AI and machine learning tools, including TensorFlow, PyTorch, and Azure Data and AI services, to elevate analytics capabilities.
• Technical Translation: Convert complex business requirements into clear technical and functional specifications to ensure accurate implementation of data solutions.
• Cross-Functional Collaboration: Work alongside various teams to integrate data insights into business processes and decision-making frameworks, enhancing the overall data competency within the organization.
• Strategic Contribution: Lead digital risk management initiatives by implementing a robust framework that adheres to industry standards (NIST, COBIT, ISO 27001) to mitigate cybersecurity threats and protect data.
• Compliance and Assessment: Ensure compliance with evolving regulatory requirements and industry standards (e.g., ADHICS, NESA, PCI-DSS, ISO 27001, ISO 27701, ISO 22301, ISO 28000, SWIFT KYC) to minimize compliance risks.
• Vendor Risk Management: Develop and execute a comprehensive strategy to manage vendor-related risks in alignment with the organization’s risk appetite and business goals.
• Required Skills for Success
• Machine Learning Development and Prototyping: Expertise in extracting datasets from SQL and serializing machine learning models.
• Data Analysis and Experimentation: Ability to conduct inferential analyses and investigate data to derive insights.
• Communication and Collaboration: Strong capability to effectively communicate machine learning and algorithm designs to cross-functional teams.
• Technical Proficiency: Skilled in scripting languages such as SQL, Python, and Spark, with experience using Azure tools (e.g., Databricks, Azure ML) and developer tools (e.g., Azure DevOps/GitHub, Docker).
• MLOps and ML Frameworks: Proficient in MLOps and LLMOps practices, with experience using ML libraries and frameworks, including TensorFlow, PyTorch, MLFlow, OpenAI, and LangChain.
• Qualifications That Equip You for the Role
  Extensive Experience: Over 15 years of experience in data science, including at least 5 years focused on developing and deploying machine learning and deep learning solutions for both batch and real-time data pipelines, along with 3+ years in a Data Science Lead position.
• Proven Impact: A demonstrated history of delivering significant business impact through analytics solutions.
• Statistical Expertise: Strong foundation in probability and statistics, encompassing machine learning, optimization, forecasting, and experimental design.