Data Science Lead | Corporate Services | Group Technology (Dubai, AE)

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Job Requisition ID: 161747

Established in the 1930s as a trading business, Al-Futtaim Group today is one of the most diversified and progressive, privately held regional businesses headquartered in Dubai, United A”rab Emirates. Structured into five operating divisions; automotive, financial services, real estate, retail and healthcare; employing more than 35,000 employees across more than 20 countries in the Middle East, Asia and Africa, Al-Futtaim Group partners with over 200 of the world’s most admired and innovative brands. Al-Futtaim Group’s entrepreneurship and relentless customer focus enables the organisation to continue to grow and expand; responding to the changing needs of our customers within the societies in which we operate.

By upholding our values of respect, excellence, collaboration and integrity; Al-Futtaim Group continues to enrich the lives and aspirations of our customers each and every day.
Overview of the role

As the Data Science Lead within the Data and Analytics team at Al-Futtaim Group (AFG), your role is pivotal in leading the development and deployment of cross-functional data science use cases. Reporting to the Head of Data Engineering & Operations, you will leverage AI and cloud technologies, including our Azure data platform, to maximize ROI through the execution of forecasting, predictive, optimization models and LLMs. 
You will evaluate diverse new data sources originating from both SAP and non-SAP systems, rapidly converting these into datasets primed for generating business insights

What you will do

• Design, document, and implement predictive models and machine learning algorithms that demonstrate clear ROI to business stakeholders. Test and refine these models rapidly in response to new data and business needs. 
• Lead early-stage discussions on data potential and predictive insights to influence project scopes and deliverables, ensuring alignment with strategic goals. 
• Architect and manage robust, scalable data pipelines to support ongoing data ingestion and analysis, optimizing for speed and data integrity. 
• Utilize advanced technologies in AI and machine learning, including TensorFlow, PyTorch, and Azure Data and AI services, to enhance analytics capabilities. 
• Translate complex business needs into clear technical and functional specifications to ensure precise implementation of data solutions. 
• Work collaboratively across functional teams to integrate data insights into business processes and decision-making frameworks, enhancing the collective data competency of the organization. 
• Strategic Contribution: Digital Risk Management, Lead the implementation of strategic initiatives and maintain a robust framework using industry standards (NIST, COBIT, ISO 27001) to mitigate cybersecurity threats and safeguard data.

• Compliance and Gap Assessment: Ensure adherence to evolving regulatory requirements and industry standards (ADHICS, NESA, PCI-DSS, ISO 27001, ISO 27701, ISO 22301, ISO 28000, SWIFT KYC), minimizing compliance risks.

• Vendor Risk Management: Develop and implement a comprehensive strategy to manage vendor-related risks aligned with the organization’s risk appetite and business objectives.

Required Skills to be successful

• Machine Learning Development and Prototyping: Pulling datasets from SQL, Serializing ML models 
• Data Analysis and Experimentation: Conducting inferential analyses and data investigations 
• Communication and Collaboration: Clearly communicating ML/algorithm designs to cross-functional teams. 
• Technical Proficiency:Proficiency in scripting languages (SQL, Python, Spark) 
• Experience with Azure tools (Databricks, Azure ML, etc.) and developer tools (Azure DevOps/GitHub, Docker)

• Experience in MLOps and ML Frameworks:Proficiency in MLOps and LLMOps practices 
• Experience with ML libraries and frameworks (TensorFlow, PyTorch, MLFlow, OpenAI, LangChain)

What equips you for the role

• 15+ years of working experience in data science, with at least 5 years working in developing and deployment ML/DL solutions focused on batch and real-time data pipelines and 3+ years working as Data Science Lead 
• Proven record of delivering business impact through analytics solutions 
• Experience with probability and statistics inclusive of machine learning, optimization, forecasting and experimental design. 

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