What Jobs are available for Data Science Manager in Dubai?

Data Science Manager - Finance | Al-Futtaim Automotive

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 Arab 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 organization 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

As a Data Science Manager(Finance) at Al-Futtaim Automotive, you will lead AI and data science initiatives that optimize financial performance, strengthen risk management, and improve business decision-making. This role focuses on advanced predictive modelling, financial forecasting, and portfolio optimization to create measurable impact across the organization

• Build and deploy predictive models for residual value optimization, credit risk scoring, probability of default, and F&I leasing pricing optimization.
• Standardize financial KPIs and risk dashboards using statistical process control and advanced visualization tools.
• Generate financial insights through time series analysis, portfolio optimization, survival analysis, and risk modelling.
• Collaborate with finance and risk teams to identify and prioritize high-potential data-driven use cases.
• Lead and mentor a team of data scientists, ensuring the delivery of scalable machine learning and AI models

• Advanced expertise in time series forecasting, regression, logistic regression, and random forests.
• Strong skills in survival analysis, neural networks, reinforcement learning, and genetic algorithms.
• Deep knowledge of portfolio optimization, risk modelling, and causal inference techniques.
• Proficiency in deep learning (CNNs, RNNs, LSTMs, Transformers) and advanced pattern recognition.
• Strong understanding of financial regulations and their impact on AI/ML model development.
• Excellent stakeholder management and ability to translate complex financial models into actionable insights

You will report to the Head of Financial Data Science and lead a team of Data Scientists and a Data Science Manager. The team operates within the Finance Department, playing a critical role in enhancing financial planning, risk management, and profitability through advanced analytics

• Bachelor’s, Master’s, or PhD in Financial Analytics, Computer Science, or related field.
• 7+ years of experience in financial analytics, data science, and machine learning.
• Hands-on expertise in advanced statistics, optimization, causal and Bayesian modelling, time series forecasting, Monte Carlo simulations, graph neural networks, and recommender systems.
• Proficient in Python, SQL, Databricks, and ML libraries (TensorFlow, PyTorch, Scikit-learn, ARIMA/SARIMA, Prophet).
• Knowledge of NLP, autoencoders, transformers, NER, computer vision (OpenCV, YOLO), and model explainability (SHAP, LIME).
• Experience with MLOps, Git, and visualization tools (Matplotlib, Seaborn, Plotly).
• Strong leadership, problem-solving, and communication skills to manage teams and deliver business impact.

About Al-Futtaim Automotive : A major division of the UAE-based Al-Futtaim Group of companies, Al-Futtaim Automotive is an industry leader with presence in 10 countries across the Middle East, Asia and Africa. Our core business activities at Al-Futtaim Automotive include distribution, manufacturing, leasing and aftersales, and we are firmly established as the regional representative of some of the world’s most iconic automotive brands: Toyota, Lexus, Honda, Jeep, Chrysler, Dodge, Volvo and RAM. We are driven by a customer-centric approach, constantly pushing the boundaries on innovation, quality standards, and value-added service across our vast universe of customers - right from motoring enthusiasts to fleet operators to contractors. Our mission is to become the leader in custom-made mobility solutions by delivering nothing less than world-class omni-channel experiences. We channel our local expertise and global trust to deliver one of the most comprehensive portfolios of mobility products and solutions, from passenger cars to SUVs, electric vehicles to high-performance motorbikes, commercial vehicles to industrial & construction equipment. What keeps the company moving forward is a 9000-member strong team, with inspiring possibilities for growth, throughout the career path. This is Al-Futtaim Automotive and we empower talent to move forward.

Overview

Data Science Manager (Operations) at Al-Futtaim Automotive leads AI and advanced analytics initiatives that transform operational performance across the business. This role focuses on predictive modelling, anomaly detection, and process optimization to drive efficiency, reduce costs, and enhance customer satisfaction.

• Build and deploy predictive models for price elasticity, predictive maintenance, churn prediction, and anomaly detection in parts utilization.
• Standardize operational KPIs and real-time reporting systems across brands using statistical process control and advanced visualization techniques.
• Deliver actionable insights on sales and operational performance using causal inference, A/B testing, and counterfactual models.
• Collaborate with cross-functional stakeholders to identify new use cases, define business cases, and prioritize high-impact initiatives.
• Lead and mentor a team of data scientists, ensuring robust MLOps practices and scalable model deployment.

• Expertise in time series analysis, regression, and survival analysis for price elasticity and churn prediction.
• Proficiency in IoT data analysis, predictive maintenance algorithms, and unsupervised learning techniques for anomaly detection.
• Strong knowledge of causal inference, A/B testing, counterfactual modelling, and optimization algorithms.
• Familiarity with deep learning frameworks and pattern recognition for complex operational data.
• Strong stakeholder engagement and the ability to turn complex data insights into operational improvements.

You will report to the Head of AI and Data Science for Operational Excellence and lead a team of Data Scientists and a Data Science Manager. The team works within the Finance Department, playing a key role in improving efficiency, reducing risk, and unlocking value across all operational functions.

• Bachelor’s, Master’s, or PhD in Computer Science, Statistics, or a related field.
• 7+ years of experience in data science, operations analytics, or AI-driven business transformation.
• Hands-on expertise with advanced statistics, optimization, survival analysis, causal and Bayesian modelling, time series forecasting, graph neural networks, and recommender systems.
• Proficient in Python, SQL, Databricks, and ML libraries (TensorFlow, PyTorch, Scikit-learn, ARIMA/SARIMA, Prophet).
• Knowledge of NLP, transformers, autoencoders, NER, computer vision (OpenCV, YOLO), and model explainability (SHAP, LIME).
• Experience with MLOps, Git, and visualization tools (Matplotlib, Seaborn, Plotly).
• Strong leadership, communication, and project management skills.

A major division of the UAE-based Al-Futtaim Group of companies, Al-Futtaim Automotive is an industry leader with presence in 10 countries across the Middle East, Asia and Africa. Our core business activities include distribution, manufacturing, leasing and aftersales, and we are the regional representative of brands such as Toyota, Lexus, Honda, Jeep, Chrysler, Dodge, Volvo and RAM. We are driven by a customer-centric approach, pushing innovation, quality standards, and value-added service across our customer base. Our mission is to become the leader in mobility solutions by delivering world-class omni-channel experiences. We employ a 9,000-member team with growth opportunities across the career path. This is Al-Futtaim Automotive and we empower talent to move forward.

Overview

MAIN OBJECTIVE OF ROLE To define and drive the enterprise strategy for extracting business value from data by leveraging advanced analytics, machine learning, and artificial intelligence to generate insights, develop predictive models, foster AI innovation, and integrate ethical and scalable AI into products, services, and decision-making processes that deliver competitive advantage.

• Leads the development and implementation of machine learning models, algorithms, and AI systems and explores innovative approaches to solving business problems using AI technologies.
• Drives continuous process improvement and optimization by staying informed about advancements in data engineering and AI, recommending new tools and technologies.
• Builds, mentors, and leads a team of data and machine learning engineers, and AI specialists by providing guidance, support, and professional development opportunities to team members.
• Develops and executes the organization’s data science and AI vision, ensuring alignment with business objectives and measurable outcomes.
• Identifies, designs, and implements AI and machine learning solutions that enhance products, services, and operational efficiency.
• Establishes frameworks for responsible, explainable, and bias-free AI use in compliance with regulations and ethical standards.
• Partners with product owners, business leaders, and data engineering teams to ensure AI initiatives are integrated, scalable, and business-driven.
• Monitors advances in AI research, tools, and technologies, proactively applying them to maintain competitive advantage.
• Defines KPIs and tracks ROI for AI initiatives to ensure value delivery and continuous improvement.
• Acts as a “data translator,” bridging technical and business domains to convert complex challenges into actionable AI-driven outcomes.

• Bachelor's Degree (3+ years)
• Degree in Information Technology, Computer Science, Data Science, or related field
• Fluent in English
• Deep understanding of data governance, compliance, and security best practices. Excellent understanding of machine learning concepts and algorithms. Proven track record of delivering AI solutions from concept to production at enterprise scale. Strong background in statistical modeling, machine learning, deep learning, and AI productization. Demonstrated success in translating business strategy into AI-driven initiatives with measurable ROI. Experience in regulated industries (e.g., Airline) preferred, with a strong understanding of ethical and compliant AI practices.
• Years with qualifications: 10 - 12 years
• Google Professional Machine Learning Engineer, AWS Certified Machine Learning – Specialty, Microsoft Certified: Azure AI Engineer Associate are an advantage

• Customer Focus
• Teamwork
• Effective Communication
• Personal Accountability & Commitment to achieve
• Resilience & Flexibility (Can do attitude)
• Decision Making
• Inspiring & Developing Others
• Strategic Thinking
• Business Acumen

Reads and complies with the ISR policies of the Company and diligently reports any weakness or incidents to the respective Line Manager or the Information Security team. Completes all required ISR awareness sessions and follows associated guidelines in the day-to-day business operations.

Effective Business Decisions Using Data Analysis

ID 257

Course: Effective Business Decisions Using Data Analysis

This interactive, applications-driven 5-day course will highlight the added value that data analytics can offer a professional as a decision support tool in management decision making. It will show the use of data analytics to support strategic initiatives; to inform on policy information; and to direct operational decision making. The course will emphasize applications of data analytics in management practice; focus on the valid interpretation of data analytics findings; and create a clearer understanding of how to integrate quantitative reasoning into management decision making. Exposure to the discipline of data analytics will ultimately promote greater confidence in the use of evidence-based information to support management decision making.

• Discussions on applications of data analytics in management
• The importance of data in data analytics
• Applying data analytical methods through worked examples
• Focusing on management interpretation of statistical evidence
• How to integrate statistical thinking into the work domain

• Explain the scope and structure of data analytics.
• Apply a cross-section of useful data analytics.
• Interpret meaningfully and critically assess statistical evidence.
• Identify relevant applications of data analytics in practice.

• Professionals in management support roles
• Analysts who typically encounter data/analytical information regularly in their work environment
• Those who seek to derive greater decision-making value from data analytics

This course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension, and retention of the information presented. The daily workshops will be highly interactive and participative. This involves regular discussion of applications as well as hands-on exposure to data analytics techniques using Microsoft Excel. Delegates are strongly encouraged to bring and analyse data from their own work domain. This adds greater relevancy to the content. Emphasis is also placed on the valid interpretation of statistical evidence in a management context.

• Day One: Setting the Statistical Scene in Management
  • Introduction; The quantitative landscape in management
  • Thinking statistically about applications in management (identifying KPIs)
  • The integrative elements of data analytics
  • Data: The raw material of data analytics (types, quality, and data preparation)
  • Exploratory data analysis using Excel (pivot tables)
  • Using summary tables and visual displays to profile sample data
• Day Two: Evidence-based Observational Decision Making
  • Numeric descriptors to profile numeric sample data
  • Central and non-central location measures
  • Quantifying dispersion in sample data
  • Examine the distribution of numeric measures (skewness and bimodal)
  • Exploring relationships between numeric descriptors
  • Breakdown analysis of numeric measures
• Day Three: Statistical Decision Making – Drawing Inferences from Sample Data
  • The foundations of statistical inference
  • Quantifying uncertainty in data – the normal probability distribution
  • The importance of sampling in inferential analysis
  • Sampling methods (random-based sampling techniques)
  • Understanding the sampling distribution concept
  • Confidence interval estimation
• Day Four: Statistical Decision Making – Drawing Inferences from Hypotheses Testing
  • The rationale of hypotheses testing
  • The hypothesis testing process and types of errors
  • Single population tests (tests for a single mean)
  • Two independent population tests of means
  • Matched pairs test scenarios
  • Comparing means across multiple populations
• Day Five: Predictive Decision Making - Statistical Modeling and Data Mining
  • Exploiting statistical relationships to build prediction-based models
  • Model building using regression analysis
  • Model building process – the rationale and evaluation of regression models
  • Data mining overview – its evolution
  • Descriptive data mining – applications in management
  • Predictive (goal-directed) data mining – management applications

Messilat is seeking a talented MLOps Engineer for our client's team. The perfect candidate will excel in deploying models, managing microservices, utilizing Docker, and maintaining Kubernetes. Our client is also exploring AI applications in customer service, cybersecurity, and compliance.

Key Responsibilities

• Transition models from development to production, ensuring scalability and high performance. Collaborate with development teams for seamless model deployment.
• Implement monitoring and maintenance strategies for deployed models to ensure ongoing accuracy and reliability.
• Maintain Kubernetes clusters to ensure high availability and performance.
• Work with cross-functional teams to understand business requirements and deliver effective machine learning solutions.
• Develop and implement strategies that optimize efficiency and data quality.

Qualifications

• Minimum of 3 years of experience in MLOps or a related field.
• Expertise in model deployment, containerization, and orchestration (e.g., Docker, Kubernetes).
• Familiarity with cloud platforms (e.g., AWS, or on-premises) for model deployment and management.
• Experience in deploying AI models and managing their lifecycle.
• Proficiency in Python for scripting and automation.
• Prior experience in addressing scalability and pricing concerns in ML operations.

Skills

• Model deployment, monitoring, Docker, Kubernetes, AWS Cloud services, on-premises deployment, collaboration.

If you are passionate about MLOps and looking for a challenging role where you can make a significant impact, we would love to hear from you. Apply today!

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.

World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.

As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle – from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.

You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments – such as product & tech, the core business verticals, trust & safety, finance and others – to enable them to be successful.

In this role, you will:

• Query large datasets with SQL and feed ML models.
• Perform data exploration to find patterns in the data and understand the state and quality of the data available.
• Utilize Python code for analyzing data and building statistical models to solve specific business problems.
• Evaluate ML models and fine tune model parameters considering the business problem behind.
• Collaborate with senior peers to Deploy ML models in production.
• Build customer-facing reporting tools to provide insights and metrics which track system performance.
• Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data
• Participate in the off-hours on call stability rotation to support live ML models

• Bachelor’s degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field.
• Statistical modelling and math
• Basic knowledge of Machine learning algorithms.
• Basic knowledge of SQL.
• Basic knowledge of visualization tools such as Periscope
• Excellent verbal and written communication.
• Strong problem solving skills.

• Ability to contribute to a platform used by more than 5M users in UAE and other platforms in the region.
• Strengthen your resume and build your network.
• Opportunity to find a full time career with the region's leading organization.
• Working in a multicultural environment with over 50 different nationalities
• Access to the Learning & Development tools and courses provided by the company.

Bayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

#dubizzle

Property Finder is the leading property portal in the Middle East and North Africa (MENA) region, dedicated to shaping an inclusive future for real estate while spearheading the region’s growing tech ecosystem. At its core is a clear and powerful purpose: To change living for good in the region.

Founded on the value of great ambitions, Property Finder connects millions of property seekers with thousands of real estate professionals every day. The platform offers a seamless and enriching experience, empowering both buyers and renters to make informed decisions. Since its inception in 2007, Property Finder has evolved into a trusted partner for developers, brokers, and home seekers. As a lighthouse tech company, it continues to create an environment where people can thrive and contribute meaningfully to the transformation of real estate in MENA.

Location : Dubai, UAE
Department : Applied AI & Data Science Team
Reports To : Head of AI & Data Science

We are looking for a highly experienced Machine Learning/Data Scientist with foundational skills in Machine Learning Engineering, and Generative AI to join our innovative AI & Data Science team. The ideal candidate will bring expertise in advanced predictive modeling, scalable data solutions, and integrating AI systems into enterprise platforms. A strong research mindset is essential to excel in this role.

This position plays a critical role in shaping the future of AI-driven decision-making at Property Finder, driving data strategy, and delivering impactful AI solutions.

• Design and implement advanced predictive and optimization models , leveraging classical ML/Statistical model, deep learning models, and modern AI techniques.
• Drive applied innovation in Large Language Models (LLMs) , Generative AI , and Agentic AI systems, exploring and developing novel applications to enhance and automate user experience, improve lead qualification, personalized recommendations, content creation, or automation and automate workflows.
• Build end-to-end model development, including experimentation, rigorous evaluation, and deployment into production environments.
• Build and maintain robust evaluation pipelines, A/B testing frameworks, and model monitoring systems to ensure performance, reliability, and fairness.
• Develop and optimize advanced analytics and visualization frameworks to support decision-making at scale.
• Collaborate with engineering teams to ensure production-grade scalability, low latency, and operational resilience of deployed models.
• Integrate trust and explainability into model design, generate confidence scores, ensure fairness, and maintain auditability.
• Continuously optimize model performance for scalability, efficiency, and real-world reliability.
• Implement MLOps and deployment best practices (CI/CD, automated workflows, model registry, versioning, and lifecycle management).
• Partner with the Data Platform and Engineering team to optimize model deployment and operational workflows.
• Work closely with the Strategy, BA, Commercial, and Product teams to align on project objectives and ensure smooth deployment of solutions.

• Education : Bachelor or above in Computer Science, Data Science, Machine Learning, or a related field.
• Experience : At least 4+ years in Data Science or MLE roles and foundational MLOps practices.
• Technical Skills :
• Working knowledge of advanced predictive modeling, optimization, scenario analysis, and statistical methodologies.
• Strong grasp of supervised/unsupervised methods, evaluation metrics, feature engineering, and model tuning.
• Proficiency in Python (pandas, NumPy, Scikit-learn); experience with PyTorch or TensorFlow for deep learning.
• Experience with API development and connecting AI systems to external platforms.
• Working knowledge in deep learning techniques, including CNNs, RNNs, and transformers.
• Hands-on experience in applied GenAI/LLMs/Agentic AI augmented with knowledge of transformer-based architectures, prompt engineering, fine-tuning, and retrieval-augmented systems.
• Experience in leveraging cloud platforms (AWS, GCP, Azure) for scalable AI solutions.
• Foundational understanding of ML pipelines and Hands-on experience in deployment processes, version control systems (e.g., Git), CI/CD workflows, and containerization tools like Docker.
• Good working knowledge of cloud platforms like AWS, GCP, or Azure.
• Soft Skills :
• Effective communication and collaboration skills, particularly in cross-functional environments.
• Strategic mindset with the ability to translate business goals into data-driven initiatives.

• Contribute to cutting-edge AI and ML projects in a dynamic and fast-paced environment.
• Collaborate with top talent across diverse teams and disciplines.
• Be part of an innovative culture that values advanced research, strategic thinking, and impactful execution.

Our promise to talent

At Property Finder, we believe talent thrives in an environment where you can be your best self. Where you are empowered to create, elevate, grow, and care. Our team is made up of the best and brightest, united by a shared ambition to change living for good in the region. We attract top talent who want to make an impact. We firmly believe that when our people grow, we all succeed.

Property Finder Guiding Principles

• Think Future First
• Data Beats Opinions, Speed Beats Perfection
• Our People, Our Power
• The Biggest Risk is Taking no Risk at All

Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.

World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.

As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle – from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.

You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments – such as product & tech, the core business verticals, trust & safety, finance and others – to enable them to be successful.

In this role, you will:

• Query large datasets with SQL and feed ML models.
• Perform data exploration to find patterns in the data and understand the state and quality of the data available.
• Utilize Python code for analyzing data and building statistical models to solve specific business problems.
• Evaluate ML models and fine tune model parameters considering the business problem behind.
• Collaborate with senior peers to Deploy ML models in production.
• Build customer-facing reporting tools to provide insights and metrics which track system performance.
• Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data
• Participate in the off-hours on call stability rotation to support live ML models

• Bachelor’s degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field.
• Statistical modelling and math
• Basic knowledge of Machine learning algorithms.
• Basic knowledge of SQL.
• Basic knowledge of visualization tools such as Periscope
• Excellent verbal and written communication.
• Strong problem solving skills.

• Ability to contribute to a platform used by more than 5M users in UAE and other platforms in the region.
• Strengthen your resume and build your network.
• Opportunity to find a full time career with the region's leading organization.
• Working in a multicultural environment with over 50 different nationalities
• Access to the Learning & Development tools and courses provided by the company.

Bayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

#dubizzle

Project description

Our client, a leading manufacturer of high-end household appliances, is expanding into new smart product lines. As part of this strategic initiative, a large‑scale global program is being implemented across the company's IP portfolio. This includes the development of new embedded software, enhancements to cloud infrastructure.

• Work directly with computer vision perception engineers, and camera ISP engineers
• Define the image quality requirements for customer use cases
• Develop image processing algorithms to optimize camera image quality for performance improvement of computer vision applications
• Develop custom ML models for visual recognition and train them from scratch
• Quantize and prune ML models
• Evaluate data using relevant metrics to increase model performance
• Implement computer vision/image processing algorithms in fast/optimal C++ code
• Implement heuristic/math algorithms and probabilistic methods for camera AI
• Research existing C++ solutions for CV logic
• Develop cross‑platform C++ code
• Cover algorithms and CV code with unit tests
• Ramp up on new technologies related to CV/ML/algorithms (not R&D)
• Integrate machine learning modules into algorithms

• Bachelor's Degree or greater in Computer Science, Software Engineering, or related field
• 3‑5 years of experience developing computer vision applications/algorithms
• Participated in at least 2 image processing / computer vision projects and 1 productized
• Image processing / computer vision background/understanding
• Strong C/C++ experience
• Experience with OpenCV and ML frameworks such as PyTorch, TensorFlow, TensorFlow Lite
• Deep understanding of neural network architectures
• Experience working with embedded devices in C++ on Linux
• Good understanding of geometry (2D/3D) and algebra
• Desire to learn new technologies
• Desire to follow test‑driven development (in CV/ML as well)

• Experience with machine learning integration, inference engines
• General machine learning understanding
• Experience building for Android/Yocto
• Experience/understanding of OpenCL/cuD, or OpenGL/Vulkan (shaders) and desire to learn other SIMD languages