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ai data scientists (cctv analytics) Jobs in Uae

ai data scientists (cctv analytics)

data analyst

senior data scientist

TMC Middle East

<div>
 
 TMC Middle East is currently engaged in a project with one of our prestigious customers in UAE.
 
 
 We are seeking a highly capable Senior Data Scientist expert to help TMC to deliver this assignment.
 
 
 
 
 
 
 About the Role:
 
 
 
 Position: Senior Data Scientist
 
 
 Location: Abu Dhabi
 
 
 Experience: 8+ Years
 
 
 Preferred: Western &amp; Diverse candidates
 
 
 
 
 
 Technical Requirements
 
 
 ● Core AI/ML: Expert proficiency in Python and standard ML libraries (TensorFlow/PyTorch,
 
 
 Scikit-learn, Pandas, NumPy). Strong grasp of both supervised and unsupervised learning
 
 
 techniques.
 
 
 ● NLP &amp; LLMs: Deep experience with transformer-based models (GPT, BERT, Llama) and
 
 
 prompt engineering techniques (few-shot learning, fine-tuning) for domain-specific tasks.
 
 
 ● Data Engineering: Proficiency in handling complex data structures (JSON, XML) and
 
 
 familiarity with database querying (SQL/NoSQL) or graph data structures. Experience with
 
 
 data extraction from specialized formats is a significant plus.
 
 
 ● Backend Awareness: Understanding of how to expose models via RESTful APIs
 
 
 (Flask/FastAPI) and integrate them into larger software architectures.
 
 
 ● Statistics: Solid understanding of statistics, probability distribution, A/B testing. Adept at
 
 
 identifying and mitigating biases in datasets.
 
 
 
 
 
 Professional Qualifications
 
 
 ● Experience: 5+ years of experience in Data Science or Machine Learning, with a proven
 
 
 track record of deploying models into production environments.
 
 
 ● Domain Adaptability: Ability to quickly grasp complex domain terminology (e.g.,
 
 
 construction regulations, defense standards, supply chain taxonomies) and translate them
 
 
 into logic.
 
 
 ● Structured Delivery: Experience working in structured delivery models
 
 
 (Agile/Sprint-based) while adhering to rigorous validation and verification standards.
 
 
 ● Collaboration: Strong communication skills to work effectively with Domain Experts,
 
 
 Backend Engineers, and Product Managers to align model outputs with real-world
 
 
 business logic.
 
 
 
 
 
 Please share your CV with the title of
 
 Senior Data Scientist
 
 
 
 Mail ID : vigneshwari.sivalingam@tmc-employeneurs.com
 
</div>

Senior Data Scientist

Yassir

<div>
 
 About Yassir
 
 
 
 Yassir is the Super App designed to make your life easier. Yassir&rsquo;s Mission is to serve Africans in the continent and its diaspora while creating economic opportunities for service providers and infusing social values. We aspire towards providing our users with the most essential services to their door by leveraging technology and a large ecosystem of partners. We at Yassir stand for: Ambition, Transparency &amp; Trust, Quality, Performance. And we are growing fast - super fast.By choosing a career at Yassir, you choose to be part of one of the most impactful, fastest-growing Tech companies in Africa.
 
 
 
 About The Role
 
 
 
 <ul>
 <li>
 Yassir is seeking a highly skilled and motivated Data Scientist, of any level, to join our Artificial Intelligence (AI) team and contribute to some of our key projects, such as Dynamic Pricing and Trip Dispatching. As a Data Scientist, you will play a crucial role in analyzing and modelling data to optimize our Machine Learning (ML) systems. Your expertise in both predictive modelling and software development will be essential in driving our solutions and providing value to Yassir. This is a very exciting opportunity, tackling some of Yassir&rsquo;s most critical problems
 
 
 
 </li>
 </ul>
 
 About The Team
 
 
 
 <ul>
 <li>
 The AI team is part of Yassir&rsquo;s central Data &amp; AI domain, which is responsible for all data related activities in the organization - from Data Engineering, Data Platform management and Data Analytics all the way to AI solutions and MLOps infrastructure development. We are a global team of Data and AI / ML experts, encompassing diverse backgrounds and skills. We strive to build state-of-the-art Data and ML infrastructure and solutions, and ultimately a Data Culture supported by responsible and democratized data access, data-driven decision making and automation. We push the envelope of what&rsquo;s feasible, we challenge each other, we support each other, and we take great pride in our work. Most of all we are value-driven to create impact from our data solutions. If you have an inherent curiosity about the fields Data and AI, a relevant background and an internal zeal and drive to contribute, please come join us!
 
 
 
 </li>
 </ul>
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Become an expert point of contact and thought leader on your scope by mastering the details and principles pertaining to it
 </li>
 <li>
 Some key areas we have to focus include: optimizing our Pricing capabilities, such as Dynamic / Surge Pricing, Discounts / Commissioning Optimization and Personalized Pricing, optimizing our Dispatching capabilities, optimizing our Fraud Detection / Revenue Leakage Prevention capabilities, optimizing our Recommendations / Personalization capabilities, amongst others
 </li>
 <li>
 Identify and propose ML opportunities related to your scope and beyond
 </li>
 <li>
 Support with requirements definition and prioritization of ML projects
 </li>
 <li>
 Collaborate with cross-functional Engineering and Product teams
 </li>
 <li>
 Champion Data Quality as a critical input component to all ML solutions and Analytics
 </li>
 <li>
 Conduct Exploratory Data Analysis and subsequent Feature Selection / Engineering
 </li>
 <li>
 Utilize Statistical and ML techniques, as appropriate, for model training
 </li>
 <li>
 Validate and tune ML models
 </li>
 <li>
 Visualize analysis / modelling results focusing on meaningful, actionable metrics and insights
 </li>
 <li>
 Deploy and test ML applications using our MLOps infrastructureMonitor ML models on their technical performance, business impact and underlying data / concept drift
 </li>
 <li>
 Explain technical solutions in a business-friendly manner, supporting Product teams in their communications and reporting
 </li>
 <li>
 Maintain and improve technical documentation of delivered solutions
 </li>
 <li>
 Support the Data &amp; AI domain in developing its technical capabilities, improving its ways of working and collaboration with other dependent teams
 </li>
 <li>
 Champion Data Culture, proactively share knowledge across teams, and participate and drive team building activities
 
 
 
 </li>
 </ul>
 
 Key Requirements - Essential
 
 
 
 <ul>
 <li>
 Solid Mathematical / Statistical / Machine Learning as well as Software Development technical skills - supported by a Masters degree or above in a relevant quantitative field such as Mathematics, Statistics, Data Science, Machine Learning, Operational Research, Computer Science, Software Engineering, Physics
 </li>
 <li>
 Comfortable in efficient, production quality Python and SQL coding at a professional setting with at least 2 years of industry experience (more years of experience would be required for more Senior roles)
 </li>
 <li>
 Comfortable with key software engineering concepts, such as code / memory profiling, code optimization, scalability, code / QA testing, cost optimization and associated best practices
 </li>
 <li>
 Comfortable with key Statistical concepts, such as statistical testing and causal analysis
 </li>
 <li>
 Analytical thinking and problem solving skills
 </li>
 <li>
 Engineering mindset focused towards delivering robust applied data science solutions
 </li>
 <li>
 Visualization skills, including experience with common Python ecosystem libraries and/or Analytics / BI tooling
 </li>
 <li>
 Familiarity and prior use of Cloud solutions and their data / ML services - at Yassir we use Google Cloud Platform (GCP), experience with which is highly preferred
 </li>
 <li>
 Mastering of the end-to-end (ML) model development lifecycle
 </li>
 <li>
 Excellent communication skills, including presentation and oral / written communication (clear articulation, concise documentation) in professional English
 </li>
 <li>
 Positive attitude and resilience
 </li>
 <li>
 Strong interpersonal skills focused on peer support, empathy, active listening, team building and stakeholder relationships building
 </li>
 <li>
 Internal drive, self-motivation and ability to work independently including own effective project management
 
 
 
 </li>
 </ul>
 
 Nice to have
 
 
 
 <ul>
 <li>
 Experience with On-demand, Mobility or Financial Services companies
 </li>
 <li>
 Experience working on ML features for Digital Products (apps, websites)
 </li>
 <li>
 Experience with one or more from: Pricing / Economics related projects and/or modelling techniques (we welcome Economics / Econometrics backgrounds and experience), Fraud Detection related projects, Dispatching related projects, Personalization related projects
 
 
 
 </li>
 </ul>
 
 Join the ride!
 
 
 
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
</div>

Mid/Senior - Data Scientist

Contango

<div>
 
 Contract duration:
 
 6 months (with a potential extension)
 
 
 
 Engagement Type:
 
 Full-time
 
 
 
 Start date:
 
 July 2026
 
 
 
 Location:
 
 Abu Dhabi (on-site)
 
 
 
 About Contango
 
 
 
 Contango is the strategic partner for transformative growth and sustained success for the ADQ portfolio. Our team excels in providing comprehensive growth solutions that combine global best practices with local market expertise. We focus on long-term value creation, empowering our clients to achieve the full scale of their aspirations. As a trusted advisor to ADQ's portfolio companies, Contango helps CEOs drive strategic growth initiatives, navigate disruptive forces, and maximize long-term value creation.
 
 
 
 Role Overview
 
 
 
 As a Senior Data Scientist, you will independently work on specific data projects and be responsible for implementing analytical solutions. You will design, build, deploy, and support end-to-end Data &amp; AI solutions. You will translate complex business challenges into scalable, production-ready analytics and machine learning systems, collaborating closely with product, data engineering, and architecture stakeholders to deliver measurable impact.
 
 
 
 Key Responsibilities
 
 
 
 
 Use Case Framing &amp; Solution Design
 
 
 
 <ul>
 <li>
 Translate client business problems into end-to-end system architectures that combine Data, ML, and software components.
 </li>
 <li>
 Lead the design of scalable, modular AI solutions, defining services, interfaces, and data flows.
 </li>
 <li>
 Make explicit trade-offs across performance, cost, latency, and maintainability.
 </li>
 <li>
 Define success metrics, SLAs, and non-functional requirements (reliability, security, scalability).
 
 
 </li>
 </ul>
 
 Data Engineering &amp; Feature Systems
 
 
 
 <ul>
 <li>
 Design and implement robust data pipelines (batch and streaming) with strong guarantees on quality, lineage, and observability.
 </li>
 <li>
 Build and manage feature pipelines and feature stores, ensuring consistency between training and inference.
 </li>
 <li>
 Collaborate with platform teams to define data models, schemas, and storage strategies.
 </li>
 <li>
 Enforce standards for data validation, testing, and monitoring within production systems.
 
 
 </li>
 </ul>
 
 Applied ML &amp; Production-Grade Development
 
 
 
 <ul>
 <li>
 Develop ML solutions using production-quality code (Python/JS), following software engineering best practices.
 </li>
 <li>
 Structure codebases into maintainable, testable modules, with clear separation of concerns.
 </li>
 <li>
 Implement unit, integration, and end-to-end tests for data and ML components.
 </li>
 <li>
 Package models and logic into deployable services (APIs, microservices, batch jobs) using modern frameworks.
 </li>
 <li>
 Balance model sophistication with system performance, latency, and operational constraints.
 
 
 </li>
 </ul>
 
 MLOps, DevOps &amp; Platform Integration
 
 
 
 <ul>
 <li>
 Build and maintain CI/CD pipelines for ML systems, including automated testing, validation, and deployment.
 </li>
 <li>
 Containerize and deploy services using Docker, Kubernetes, and cloud-native tooling.
 </li>
 <li>
 Implement model versioning, experiment tracking, and artifact management.
 </li>
 <li>
 Design monitoring and observability systems (logs, metrics, alerts) for both data and model performance.
 </li>
 <li>
 Automate retraining, rollback, and release strategies to ensure system resilience.
 
 
 </li>
 </ul>
 
 System Reliability, Scalability &amp; Security
 
 
 
 <ul>
 <li>
 Design systems for high availability, fault tolerance, and horizontal scalability.
 </li>
 <li>
 Optimize performance across data pipelines and inference services (latency, throughput, cost).
 </li>
 <li>
 Apply secure coding practices, access controls, and data protection standards.
 </li>
 <li>
 Manage technical debt and ensure long-term maintainability of production systems.
 
 
 </li>
 </ul>
 
 Documentation, Standards &amp; Engineering Excellence
 
 
 
 <ul>
 <li>
 Produce developer-focused documentation (APIs, architecture diagrams, runbooks).
 </li>
 <li>
 Establish and enforce coding standards, review processes, and engineering best practices.
 </li>
 <li>
 Build reusable libraries, SDKs, and internal frameworks to accelerate delivery.
 </li>
 <li>
 Drive continuous improvement in engineering maturity, tooling, and delivery practices across the consultancy.
 
 
 </li>
 </ul>
 
 Required Experience And Qualifications
 
 
 
 <ul>
 <li>
 Prior experience at management consulting firms and/or Big Tech is an advantage.
 </li>
 <li>
 Client-serving experience is an advantage.
 </li>
 <li>
 5+ years of experience in data science or a related analytical field.
 </li>
 <li>
 5+ years delivering end-to-end analytics/ML solutions from problem framing through deployment and ongoing monitoring in production.
 </li>
 <li>
 Experience applying software engineering methodologies and best practices, including coding standards, code reviews, build processes, testing, and security.
 </li>
 <li>
 Prior experience in developing AI solutions on public cloud services is an advantage.
 </li>
 <li>
 Bachelor&rsquo;s degree (Master&rsquo;s preferred) in a quantitative field (Computer Science, Data Science, Statistics, Mathematics, Engineering).
 </li>
 <li>
 Technical Expertise:
 </li>
 <ul>
 <li>
 Coding &amp; data querying: Python (pandas/NumPy) and SQL; writing clean, testable code with Git.
 </li>
 <li>
 Statistics &amp; experimentation: Probability/statistics, hypothesis testing, regression, and A/B testing/experimental design.
 </li>
 <li>
 ML modelling: Feature engineering, model selection, cross-validation, metrics, and hyperparameter tuning (supervised/unsupervised).
 </li>
 <li>
 Data prep &amp; analysis: ETL/EDA, data cleaning, handling missing/outliers, and building insight narratives with visuals.
 </li>
 </ul>
 </ul>
</div>

Senior Data Scientist (6 months contract)

<div>Contract duration: 6 months (with a potential extension) 
Engagement Type: Full-time 
Start date: July 2026 
Location: Abu Dhabi (on-site) 
About Contango:
Contango is the strategic partner for transformative growth and sustained success for the ADQ portfolio. Our team excels in providing comprehensive growth solutions that combine global best practices with local market expertise. We focus on long-term value creation, empowering our clients to achieve the full scale of their aspirations. As a trusted advisor to ADQ's portfolio companies, Contango helps CEOs drive strategic growth initiatives, navigate disruptive forces, and maximize long-term value creation.
Role Overview
As a Senior Data Scientist, you will independently work on specific data projects and be responsible for implementing analytical solutions. You will design, build, deploy, and support end-to-end Data &amp; AI solutions. You will translate complex business challenges into scalable, production-ready analytics and machine learning systems, collaborating closely with product, data engineering, and architecture stakeholders to deliver measurable impact. 
Key Responsibilities
Use Case Framing &amp; Solution Design<ul><li>
Translate client business problems into end-to-end system architectures that combine Data, ML, and software components.</li><li>
Lead the design of scalable, modular AI solutions, defining services, interfaces, and data flows.</li><li>
Make explicit trade-offs across performance, cost, latency, and maintainability.</li><li>
Define success metrics, SLAs, and non-functional requirements (reliability, security, scalability).</li></ul>
Data Engineering &amp; Feature Systems<ul><li>
Design and implement robust data pipelines (batch and streaming) with strong guarantees on quality, lineage, and observability.</li><li>
Build and manage feature pipelines and feature stores, ensuring consistency between training and inference.</li><li>
Collaborate with platform teams to define data models, schemas, and storage strategies.</li><li>
Enforce standards for data validation, testing, and monitoring within production systems.</li></ul>
Applied ML &amp; Production-Grade Development<ul><li>
Develop ML solutions using production-quality code (Python/JS), following software engineering best practices.</li><li>
Structure codebases into maintainable, testable modules, with clear separation of concerns.</li><li>
Implement unit, integration, and end-to-end tests for data and ML components.</li><li>
Package models and logic into deployable services (APIs, microservices, batch jobs) using modern frameworks.</li><li>
Balance model sophistication with system performance, latency, and operational constraints.</li></ul>
MLOps, DevOps &amp; Platform Integration<ul><li>
Build and maintain CI/CD pipelines for ML systems, including automated testing, validation, and deployment.</li><li>
Containerize and deploy services using Docker, Kubernetes, and cloud-native tooling.</li><li>
Implement model versioning, experiment tracking, and artifact management.</li><li>
Design monitoring and observability systems (logs, metrics, alerts) for both data and model performance.</li><li>
Automate retraining, rollback, and release strategies to ensure system resilience.</li></ul>
System Reliability, Scalability &amp; Security<ul><li>
Design systems for high availability, fault tolerance, and horizontal scalability.</li><li>
Optimize performance across data pipelines and inference services (latency, throughput, cost).</li><li>
Apply secure coding practices, access controls, and data protection standards.</li><li>
Manage technical debt and ensure long-term maintainability of production systems.</li></ul>
Documentation, Standards &amp; Engineering Excellence<ul><li>
Produce developer-focused documentation (APIs, architecture diagrams, runbooks).</li><li>
Establish and enforce coding standards, review processes, and engineering best practices.</li><li>
Build reusable libraries, SDKs, and internal frameworks to accelerate delivery.</li><li>
Drive continuous improvement in engineering maturity, tooling, and delivery practices across the consultancy.</li></ul>
Required Experience and Qualifications<ul><li>
Prior experience at management consulting firms and/or Big Tech is an advantage.</li><li>
Client-serving experience is an advantage.</li><li>
5+ years of experience in data science or a related analytical field.</li><li>
5+ years delivering end-to-end analytics/ML solutions from problem framing through deployment and ongoing monitoring in production.</li><li>
Experience applying software engineering methodologies and best practices, including coding standards, code reviews, build processes, testing, and security.</li><li>
Prior experience in developing AI solutions on public cloud services is an advantage.</li><li>
Bachelor&rsquo;s degree (Master&rsquo;s preferred) in a quantitative field (Computer Science, Data Science, Statistics, Mathematics, Engineering).</li><li>
Technical Expertise:<ul><li>
Coding &amp; data querying: Python (pandas/NumPy) and SQL; writing clean, testable code with Git.</li><li>
Statistics &amp; experimentation: Probability/statistics, hypothesis testing, regression, and A/B testing/experimental design.</li><li>
ML modelling: Feature engineering, model selection, cross-validation, metrics, and hyperparameter tuning (supervised/unsupervised).</li><li>
Data prep &amp; analysis: ETL/EDA, data cleaning, handling missing/outliers, and building insight narratives with visuals.</li></ul></li></ul></div>

DICETEK LLC

<div><h1 class="jobSectionHeader">Role Purpose</h1>
The Senior Data Scientist will lead the development, optimization, and deployment of advanced card fraud detection models for issuing and acquiring businesses. This role involves end-to-end model lifecycle management, including training, hosting, evaluation, and deployment using SAS SFD and modern MLOps practices. The candidate will work closely with fraud risk, data engineering, and technology teams to ensure robust, scalable, and high-performing solutions.<h1 class="jobSectionHeader">
Key Responsibilities</h1><ul><li>Card Fraud Model Development &amp; Optimization: Design, develop, and optimize card fraud detection models for issuing and acquiring portfolios. Implement advanced statistical, machine learning, and AI techniques to improve fraud detection accuracy and precision and minimizing false positives.</li><li>Model Hosting &amp; Deployment: Deploy models using SAS SFD and integrate with production systems. Ensure seamless hosting and scalability of models across multiple environments.</li><li>MLOps &amp; Automation: Establish and maintain MLOps pipelines for continuous integration, deployment, and monitoring of fraud models. Automate model retraining and performance tracking processes.</li><li>Evaluation &amp; Testing: Conduct rigorous model validation, stress testing, and performance benchmarking. Collaborate with fraud operations teams to ensure models meet business and regulatory requirements.</li><li>Collaboration &amp; Stakeholder Management: Partner with fraud risk, data engineers, IT and business teams to deliver end-to-end solutions. Communicate insights and recommendations to senior management and business stakeholders.</li></ul><h1 class="jobSectionHeader"> 
Required Skills &amp; Qualifications</h1><ul><li>Education: Master&rsquo;s or Ph.D. in Data Science, Statistics, Computer Science, or related field.</li><li>Technical Skills: Strong proficiency in SAS (including SAS SFD), Python, and SQL. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with MLOps tools and practices (e.g., MLflow, Kubeflow, CI/CD pipelines). Deep understanding of card fraud detection techniques and transaction data.</li><li>Experience: 7+ years in data science roles, with at least 3 years in card fraud modeling. Proven track record of deploying models in production environments.</li><li>Soft Skills: Strong analytical and problem-solving skills. Excellent communication and stakeholder management abilities.</li></ul><h1 class="jobSectionHeader"> 
Preferred Qualifications</h1><ul><li>Experience in banking or payments industry.</li><li>Familiarity with cloud platforms (AWS, Azure, GCP) for model hosting and deployment.</li><li>Knowledge of regulatory compliance in fraud risk management.</li></ul></div>

Senior Fraud Data Scientist

Insight

<div>
 
 About The Role
 
 
 
 As a Data Scientist, you will play a key role in transforming complex data into actionable insights that drive business value for our clients. Working within a global delivery model, you will collaborate closely with engineering teams and stakeholders to design, build, and deploy advanced analytics and machine learning solutions.
 
 
 This is an exciting opportunity to work with cutting-edge technologies in a collaborative, fast-paced environment, contributing to high-impact projects across multiple industries.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Analyse and interpret large, complex datasets from multiple sources
 </li>
 <li>
 Apply data mining, machine learning, and statistical techniques to solve business problems
 </li>
 <li>
 Design and build predictive models and algorithms
 </li>
 <li>
 Identify valuable data sources and automate data collection processes
 </li>
 <li>
 Pre-process structured and unstructured data for analysis
 </li>
 <li>
 Discover patterns, trends, and insights to support decision-making
 </li>
 <li>
 Develop and present insights using data visualisation tools
 </li>
 <li>
 Collaborate with client and internal engineering teams to integrate models into applications
 </li>
 <li>
 Recommend data-driven solutions and strategies to business challenges
 
 
 
 </li>
 </ul>
 
 Essential Experience &amp; Skills
 
 
 
 <ul>
 <li>
 Proven experience in a Data Scientist or similar role
 </li>
 <li>
 Strong knowledge of machine learning algorithms and techniques
 </li>
 <li>
 Proficiency in Python or R
 </li>
 <li>
 Experience with data science libraries/tools (e.g. NumPy, Weka, MatLab)
 </li>
 <li>
 Experience with data visualisation tools and query languages
 </li>
 <li>
 Experience working with NoSQL databases (MongoDB, Cassandra, HBase)
 </li>
 <li>
 Strong experience handling structured and unstructured data.
 
 
 
 </li>
 </ul>
 
 Core Competencies
 
 
 
 <ul>
 <li>
 Strong analytical and statistical problem-solving skills
 </li>
 <li>
 Solid foundation in mathematics and statistics
 </li>
 <li>
 Ability to translate complex data into business insights
 </li>
 <li>
 Excellent communication skills, with the ability to engage stakeholders at all levels
 </li>
 <li>
 Critical thinking and a proactive, solution-oriented mindset
 </li>
 <li>
 Collaborative team player with strong interpersonal skills
 </li>
 </ul>
</div>

Data Scientist

Explore 1033+ Senior data scientist in Uae this July. Find roles across top companies and apply now to boost your career.

1033 senior data scientist jobs In Uae

Senior Data Scientist

Mid/Senior - Data Scientist

Senior Data Scientist (6 months contract)

Senior Data Scientist (6 months contract)

Senior Fraud Data Scientist

Senior Fraud Data Scientist

Data Scientist