60 Predictive Modeling jobs in Dubai

The company is seeking a senior data scientist to lead our growth team and accelerate our strategies across multiple dimensions.

This leader will drive business impact through the design, execution, and interpretation of experiments, empowering product, marketing, and operations teams to make data-informed decisions.

• Define and execute a comprehensive data strategy that aligns with the company's goals, leveraging data to drive business decisions and achieve strategic objectives.
• Lead cross-functional teams to design and implement innovative data-driven products and analytics insights, to deliver measurable impact on business outcomes.

• A minimum of 8-10 years of professional experience in data science, including leadership roles in data science teams or consulting.
• A Ph.D. or Master's degree in a relevant field such as computer science, statistics, data science, or a related discipline.
• Proven experience in leading and managing managers and a demonstrated ability to foster a high-performance team culture.

• Competitive compensation package.
• Opportunities for career growth and professional development.

This is a Machine Learning Engineer position that involves maintaining and developing scoring models, production systems, and high-availability operations. As part of the team, you will partner with data scientists to operationalize models and ensure efficient data flows.

• Maintain and develop credit scoring models, production systems, and high-availability operations.
• Work closely with data scientists to operationalize models and ensure efficient data flows.
• Monitor, troubleshoot, and rectify issues in deployed credit scoring models.
• Manage AzureML pipelines and Databricks workflows for model retraining, batch scoring, and real-time inference.
• Ensure 24/7 uptime of scoring APIs serving clients; implement failover systems and load balancing.
• Oversee QA/UAT processes for model updates, including back-testing, shadow deployments, and canary releases.
• Maintain audit trails for model versions, inputs/outputs, and performance metrics. Support Compliance and Audit with creation of logs when requested.
• Lead troubleshooting of scoring engine failures with SLAs for financial institution clients.
• Tune AzureML/Databricks clusters for cost-performance efficiency at scale.
• Ensure vendor support completes work as per scope and SLAs. Rectify any vendor delivery issues.

1. Bachelor's degree or equivalent in a related field.
2. Educational specialization or master's degree in computer science, software engineering.
3. Proficient in English.
4. Preferred proficiency in Arabic.
5. In-depth knowledge of React Native and Next JS and related modules, components, and libraries.
6. Preferred in-depth knowledge of SiteCore or experience integrating with SiteCore.

1. Bachelor's/master's in computer science, engineering, data science, or a related field.
2. 2+ years of data science or software engineering experience.
3. 2+ years of production ML operations experience, MLOps lifecycle management, including monitoring, retraining, and model versioning.
4. Strong problem-solving skills and the ability to resolve issues efficiently.
5. CI/CD for ML systems using tools such as Azure DevOps, GitHub Actions, MLflow, and other similar tools.
6. Ability to adapt ML workflows across different cloud environments (Azure, AWS, GCP) as needed.

1. Practical experience in cloud-based ML platforms such as AzureML, Databricks, or equivalent (e.g., SageMaker, Vertex AI), with a preference for Azure.
2. Python/PySpark for model debugging and patching. Working knowledge of Scikit-Learn and NumPy.
3. Deep understanding of credit scoring systems: feature engineering, scorecard interpretation, and output validation.
4. Credit bureau data structures (tradelines, inquiries, public records).
5. Model risk management (MRM) standards.
6. Azure Solutions Architect or MLOps certifications.
7. Experience with financial services-grade SLAs (99.9% uptime) and outage management.
8. Knowledge of containerization (Docker, Kubernetes, AKS, or similar orchestration tools).
9. Practical experience with Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS) / Azure Blob Storage.
10. Knowledge of new and upcoming AI tools.
11. Excellent written and verbal communication skills in English.
12. Strong interpersonal skills with the ability to engage and build relationships.
13. Crisis management under pressure.
14. Cross-functional collaboration with data science/risk teams.
15. Strong organizational skills with the ability to manage multiple tasks and projects simultaneously.
16. Ability to develop and document procedures, roles, and guidelines.
17. Security and Compliance, especially in financial services, mentioning data security, PII handling, and compliance with regulations.

As a key member of our team, you will play a pivotal role in driving innovation and excellence in the banking sector.

The ideal candidate will have a strong background in data science, with expertise in AI/ML and statistical modeling. They will be responsible for analyzing complex banking products to inform strategic decision-making.

Key responsibilities include:

• Developing and implementing data-driven solutions to enhance core banking processes.
• Leading analytics projects to drive growth and innovation in the industry.

The successful candidate will have:

• 7+ years experience in data science, with a focus on AI/ML and statistical modeling.
• A strong understanding of banking operations and terminology.
• Leadership experience in regulated environments.

We are seeking a highly skilled professional who possesses:

• Expertise in AI/ML and statistical modeling.
• Strong analytical and problem-solving skills.
• Effective communication and leadership skills.

This role offers a unique opportunity to work alongside passionate colleagues who share your ambition to redefine excellence in banking. You will have the chance to:

• Contribute to cutting-edge projects that drive innovation and growth.
• Develop your skills and expertise in a dynamic and supportive environment.

If you are a motivated and ambitious professional looking to make a real impact in the banking sector, we encourage you to apply for this exciting opportunity.

Embark on a journey where your unique contributions are celebrated, and your professional growth is embraced. At ADCB, we nurture a diverse, inclusive community where every voice is valued.

About the business area

GBS is a group of highly skilled and talented professionals who form an essential part of ADCB's continued journey of success. With a proud history of commitment, innovation and delivery, GBS constantly strives for excellence whilst ensuring the highest standards of quality and risk awareness. Each and every member of the GBS family plays an integral role in driving ADCB's strategy, growth and digital evolution by working closely with our valued business partners to achieve exceptional customer experience through our outstanding service and support.

We are actively seeking an ambitious professional to join our team at ADCB to work alongside passionate colleagues who share your ambition to redefine excellence in UAE banking.

In this role, your key responsibilities include:

• Analyze complex banking products and services for strategic decision-making.
• Leverage Artificial Intelligence (AI)/Machine Learning (ML) to enhance core banking processes and digital journeys.
• Leads banking analytics projects to drive business growth and innovation.
• Design and deploy advanced AI/ML models to optimize banking operations and customer journeys
• Build scalable ML pipelines using Azure AI Foundry or AWS SageMaker
• Fine-tune generative AI models using Low-Rank Adaptation (LoRA), Parameter-efficient fine-tuning (PEFT), and multimodal architectures
• Conduct A/B testing and statistical inference.
• Collaborate with engineers for containerized Continuous Integration (CI)/ Continuous Deployment (CD)
• Monitor model performance using Machine Learning Operations (MLOps) and Large Language Models (LLM) metrics Bilingual Evaluation Understudy (BLEU), ROUG.

The ideal candidate should have the following experience:

• Minimum 7 years of experience in data science, with proven expertise in AI/ML, statistical modeling, and cloud-based deployments
• Strong background in banking processes, operations, terminologies, generative AI, and Machine Learning Operations (MLOps) is essential
• Experience leading cross-functional teams and delivering scalable, production-grade solutions in a regulated, data-driven environment is highly preferred
• Bachelor's degree in quantitative field such as Computer Science, Artificial Intelligence, Software Engineering, Statistics, Mathematics or related field required
• Master's degree or equivalent in AI/ML is preferred
• Advanced Python and ML Development
• Statistical Analysis and Experimentation
• Machine Learning and MLOps
• Generative AI and LLMs
• Cloud-based ML Pipelines (Azure/AWS)
• Data Visualization and Dashboarding
• DevOps & CI/CD Practices

What we offer:

Comprehensive Benefits Package: This includes market-leading medical insurance, group life and personal accident insurance, paid leave and leave airfare, employee preferential rates on loans and finance facilities, staff discounts and offers, and children education assistance (for certain job levels).

Flexible and Remote Working Options: We understand the importance of work-life balance and offer flexible working arrangements, subject to eligibility and job requirements.

Learning and Development Opportunities: We value and facilitate continuous learning and personal development, through a variety of exciting learning opportunities, such as structured instructor-led courses, a comprehensive e-Learning catalog, on-the-job training and professional development programs.

At ADCB, we are dedicated to creating a respectful, caring and disciplined work environment that aligns with your career ambitions.

As a Data Science Manager (Operations) at Al-Futtaim Automotive, you will lead 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 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.

• Not Applicable

• Full-time

• Engineering and Information Technology

• Retail

As a Data Science Manager (Customer) at Al-Futtaim Automotive, you will lead customer-centric AI and advanced analytics initiatives that drive marketing performance and enhance the customer experience. This role focuses on building predictive models, customer insights, and hyper-personalization solutions that create measurable business impact.

• Build and deploy predictive models such as lead scoring, precision marketing, marketing attribution, customer segmentation, and hyper-personalization.
• Standardize and optimize marketing performance KPIs across brands using advanced statistical methods and data visualization.
• Deliver actionable customer insights through cohort analysis, customer lifetime value modelling, churn prediction, and campaign performance analysis.
• Collaborate with stakeholders to identify, define, and prioritize high-impact use cases supported by data-driven business cases.
• Lead and mentor a team of data scientists to deliver scalable AI / ML solutions that directly improve marketing ROI and customer experience.

• Advanced knowledge of ensemble methods, gradient boosting, uplift modelling, and multi-arm bandits for marketing optimization.
• Expertise in attribution models (Markov chains, Shapley values), clustering techniques, recommender systems, and hyper-personalization.
• Proficiency in NLP, reinforcement learning, cohort analysis, lifetime value modelling, and churn prediction.
• Strong problem-solving skills and the ability to translate complex data science solutions into business value.
• Excellent stakeholder management, communication, and project management capabilities.

You will report to the Head of Customer Data Science and lead a small team comprising a Data Science Manager and Data Scientists. The team plays a pivotal role within the Finance Department at Al-Futtaim Automotive, driving innovation in customer analytics and marketing science.

• Bachelor's, Master's, or PhD in Marketing Analytics, Computer Science, or a related field.
• 7+ years of experience in customer analytics, data science, and AI / ML solutions.
• Hands-on expertise with machine learning techniques including CNNs, RNNs, LSTMs, time series forecasting, survival analysis, graph neural networks, Bayesian and causal modelling.
• Skilled in Python, SQL, Databricks, and modern ML libraries (scikit-learn, TensorFlow, PyTorch, Prophet, ARIMA / SARIMA).
• Proficient in CRM systems, marketing analytics platforms, and MLOps practices.
• Experience with LLMs, RAGs, and modern AI-based recommendation systems.
• Strong leadership skills to manage and mentor a data science team.

The Field Engineer is responsible for working with customers at every stage of their relationship with the organization, from initial evaluations to enterprise-wide deployments. This involves helping customers design, build, validate, and run their Data Science and AI Platforms.

The ideal candidate will have strong technical abilities, adaptability, inventiveness, and excellent communication skills. They will be able to work with clients on traditional big data technologies such as SQL data warehouses, as well as helping them discover and implement cutting-edge tools like Spark on Kubernetes, cloud-based elastic compute engines, and GPUs.

This role requires a deep understanding of customer requirements in terms of scalability, availability, and security, and the ability to provide architecture recommendations accordingly.

The Field Engineer will also be responsible for deploying Dataiku in a variety of technical environments, automating operation, installation, and monitoring of the Data Science ecosystem components, collaborating with revenue and customer teams to deliver a consistent experience to customers, and driving technical success by being a trusted advisor to customers and internal account teams.

• Design, build, and validate Data Science and AI Platforms for customers
• Deploy Dataiku in various technical environments
• Automate operation, installation, and monitoring of Data Science ecosystem components
• Collaborate with revenue and customer teams to deliver a consistent experience to customers
• Drive technical success by being a trusted advisor to customers and internal account teams

The ideal candidate will have the following skills and qualifications:

• Professional experience with at least one cloud-based service (AWS, GCP, or Azure)
• Hands-on experience with the Kubernetes ecosystem for setup, administration, troubleshooting, and tuning
• Familiarity with Ansible or other application deployment tools (Terraform, CloudFormation, etc.)
• Experience with cloud-based Data Warehouses and Data Lakes (Snowflake, Databricks)
• Some experience with Python
• Grit when faced with technical issues
• Comfort and confidence in client-facing interactions
• Ability to work both pre- and post-sale

We offer a dynamic and innovative work environment that values collaboration, creativity, and personal growth. Our team is passionate about shaping the future of AI and we're looking for like-minded individuals to join us on this journey.

As a Field Engineer, you'll have the opportunity to work with a wide range of technologies, including big data, machine learning, and artificial intelligence. You'll also have access to ongoing training and development opportunities to help you grow in your career.

If you're interested in joining our team, please submit your application through our website. We look forward to hearing from you!

A software development company is looking for a talented, long-term Lead DS Researcher.

We’re looking for a Lead Data Science Researcher who thrives in research-heavy environments and enjoys exploring uncharted territory with the support of a strong technical team.

This is a unique opportunity to drive forward new ideas and applications, not just optimize existing ones.

About the company

Company Top Remote Talent

The company is a team of experts providing analytical services to healthcare clients. You will join an international team of first class professionals who are passionate to create products that improve quality of medical services.

Responsibilities

You will lead a compact team of two data scientists, guiding them on high-impact research initiatives and experimental projects. Your role will involve pushing the boundaries of applied machine learning — especially in the context of medical and clinical data — and turning complex problems into innovative solutions.

Requirements

**What we’re looking for:**Exceptional analytical and statistical skills-comfortable with uncertainty, inference, and experimentation;

Strong background in different areas of ML (traditional classification and regression techniques, recommender systems, text data, clustering, etc.);

Solid experience with deep learning frameworks like PyTorch or TensorFlow;

Excellent Python skills (beyond Jupyter Notebooks) - ability to build clean, testable, production-ready code;

Familiarity with medical or life science data is a strong plus;

Expertise in SQL, Pandas, Scikit-learn, and modern data workflows;

Comfortable working in Google Cloud Platform (GCP) environments.

**Bonus points for experience with:**State-of-the-art NLP models, Transformers, Agentic Approaches for mixed (temporal and text) data analysis and summarization;

Experience with pipeline orchestration tools like Airflow, Argo, etc.;

Proven Experience with Anomaly Detection and Forecasting with explainability for temporal and mixed data;

Intermediate+ English — ability to participate in written discussions with international teams and clients.

Working conditions

**Benefits:**Join a mission-driven team working at the intersection of data, medicine, and impact;

Work on meaningful challenges with long-term value for public health and healthcare quality;

Collaborate with top-tier experts in a culture that values curiosity, autonomy, and innovation;

Fully remote-friendly setup with flexibility and trust at the core.

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We are seeking a highly skilled Senior Data Scientist to join our team. As a key member of our data science group, you will be responsible for leading the development of strategic data science engagements with key clients and lines of business.

This is an excellent opportunity to leverage your expertise in advanced analytics and data governance to drive business growth and improve operational efficiency.