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Senior Data Science Manager

Discovered MENA

UAE · On-site Senior Today

About the role

Senior Data Science Manager - Financial Services, Abu Dhabi

Discover the Opportunity:

We’re partnering with a leading financial services organisation in Abu Dhabi that is investing heavily in data science, machine learning, and AI to drive transformation across its core business functions.

This is a senior leadership role focused on delivering high-impact data science initiatives across areas such as customer analytics, risk, credit, and operations. You will play a key role in translating complex business challenges into scalable data science solutions, driving measurable outcomes across a highly regulated environment.

This opportunity combines strategic ownership with hands-on technical leadership, enabling you to shape both the data science roadmap and the deployment of production-grade AI solutions.

Discover the Responsibilities: • Lead the design, development, and deployment of advanced data science and machine learning models to drive business outcomes across multiple domains • Apply a range of techniques including supervised, unsupervised, and time-series modelling to solve complex business problems using structured and semi-structured data • Own the end-to-end data science lifecycle, including feature engineering, model development, validation, benchmarking, and deployment • Conduct experimentation using A/B testing, statistical analysis, and hypothesis testing to measure model performance and business impact • Collaborate closely with engineering and technology teams to ensure models are production-ready and integrated through CI/CD pipelines • Monitor model performance, data drift, and stability, ensuring ongoing reliability, fairness, and compliance with regulatory requirements • Engage with stakeholders across the business to identify opportunities and embed data-driven decision-making into core processes • Lead and mentor data science teams, driving delivery standards, capability development, and best practices • Drive adoption of data science solutions through structured change management, stakeholder engagement, and communication

Discover the Requirements: • 9+ years of experience in data science, machine learning, or advanced analytics roles • Strong experience applying AI/ML techniques within complex, data-driven environments, ideally within financial services • Proven experience leading teams and delivering production-grade data science solutions in regulated environments • Strong hands-on expertise in Python, statistical modelling, and machine learning techniques • Experience with Generative AI, LLMs, and MLOps frameworks • Experience building and deploying models on cloud platforms such as AWS or Azure • Strong understanding of experimentation, model validation, and performance monitoring • Experience working in cross-functional teams and collaborating with business and technology stakeholders • Bachelor’s degree in Computer Science, Artificial Intelligence, Mathematics, Statistics, or a related field (Master’s preferred)

Requirements

  • 9+ years of experience in data science, machine learning, or advanced analytics roles
  • Strong experience applying AI/ML techniques within complex, data-driven environments
  • Proven experience leading teams and delivering production-grade data science solutions
  • Strong hands-on expertise in Python, statistical modelling, and machine learning techniques
  • Experience with Generative AI, LLMs, and MLOps frameworks
  • Experience building and deploying models on cloud platforms
  • Strong understanding of experimentation, model validation, and performance monitoring
  • Experience working in cross-functional teams and collaborating with business and technology stakeholders
  • Bachelor’s degree in Computer Science, Artificial Intelligence, Mathematics, Statistics, or a related field

Responsibilities

  • Lead the design, development, and deployment of advanced data science and machine learning models
  • Apply a range of techniques including supervised, unsupervised, and time-series modelling
  • Own the end-to-end data science lifecycle
  • Conduct experimentation using A/B testing, statistical analysis, and hypothesis testing
  • Collaborate closely with engineering and technology teams
  • Monitor model performance, data drift, and stability
  • Engage with stakeholders across the business
  • Lead and mentor data science teams
  • Drive adoption of data science solutions

Skills

Data ScienceMachine LearningAIPythonStatistical ModellingGenerative AILLMsMLOpsCloud PlatformsExperimentationModel ValidationPerformance Monitoring

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