data scientist

senior data engineer

applied ai engineer

senior ai engineer

senior data scientist

ai data scientists cctv analytics

DICETEK LLC

<div>The resources will support development and deployment of computer vision and video analytics solutions for CCTV use cases such as:<ul><li>
Queue monitoring and wait-time estimation</li><li>
Crowd and anomaly detection</li><li>
Operational insights generation</li></ul><h3 class="jobSectionHeader"> 
Required Skill Set</h3>
We are specifically looking for profiles with:<ul><li>
Strong experience in Computer Vision, Machine Learning, and Video Analytics</li><li>
Hands-on expertise in Python, TensorFlow, PyTorch, Scikit-learn</li><li>
Experience with object detection, tracking, and image processing</li><li>
Strong working knowledge of NVIDIA ecosystem (Jetson, TensorRT, DeepStream)</li><li>
Proven experience in edge deployment and on-prem AI environments</li><li>
Understanding of MLOps, model optimization, and monitoring</li><li>
Prior exposure to CCTV / surveillance analytics use cases (highly preferred)</li></ul> 
Skills: Computer Vision , CCTV Monitoring</div>

AI Data Scientists (CCTV Analytics)

Dicetek LLC

<div>
 The resources will support development and deployment of
 
 computer vision and video analytics solutions
 
 for CCTV use cases such as:
 
 
 <ul>
 <li>
 Queue monitoring and wait-time estimation
 </li>
 <li>
 Crowd and anomaly detection
 </li>
 <li>
 Operational insights generation
 
 
 </li>
 </ul>
 Required Skill Set
 
 
 
 We Are Specifically Looking For Profiles With
 
 
 
 <ul>
 <li>
 Strong experience in Computer Vision, Machine Learning, and Video Analytics
 </li>
 <li>
 Hands-on expertise in Python, TensorFlow, PyTorch, Scikit-learn
 </li>
 <li>
 Experience with object detection, tracking, and image processing
 </li>
 <li>
 Strong working knowledge of NVIDIA ecosystem (Jetson, TensorRT, DeepStream)
 </li>
 <li>
 Proven experience in edge deployment and on-prem AI environments
 </li>
 <li>
 Understanding of MLOps, model optimization, and monitoring
 </li>
 <li>
 Prior exposure to CCTV / surveillance analytics use cases (highly preferred)
 </li>
 </ul>
</div>

Presight

<div>
 
 
 Job Description: Lead Engineer - Data Centre &amp; Smart Infrastructure
 
 
 
 
 Location: Abu Dhabi
 
 
 
 
 About Presight
 
 
 
 
 
 
 Presight &mdash; ADX-listed, G42-backed, and the region's leading GenAI analytics company &mdash; is hiring a Solution Architect who is equally comfortable drawing integration blueprints and sitting in front of a client boardroom.
 
 
 This is not a purely pre-sales or design role. We need someone who has lived inside data centre programmes from concept through commissioning, owned stakeholder relationships end-to-end, and can still roll up their sleeves when it matters.
 
 
 
 
 
 
 The Opportunity
 
 
 
 We are seeking a highly experienced, hands-on Lead Engineer to drive the design, integration, and delivery of complex smart infrastructure solutions across data centres, SCADA, BMS/DCIM, IoT, and enterprise AI platforms. This role demands an ideal blend of deep technical expertise and delivery leadership &mdash; someone who can own end-to-end engineering outcomes while collaborating across multi-vendor, cross-functional teams. In later project phases, the role will progressively take on project management responsibilities, steering delivery planning, stakeholder coordination, and operational handover.
 
 
 
 Responsibilities
 
 
 <ul>
 <li>
 Lead end-to-end solution design and implementation for integrated systems spanning data centres, SCADA/OT, BMS, CCTV, access control, fire alarm, and AI/analytics platforms.
 </li>
 <li>
 Translate business requirements into scalable, secure, and high-performance architectures, ensuring alignment with business objectives and AI-driven solutions.
 </li>
 <li>
 Define and manage integration architecture across multi-vendor platforms, including APIs, middleware, data pipelines, and OT/IoT protocols (BACnet, Modbus, MQTT, REST).
 </li>
 <li>
 Develop and review high-level and low-level design documents (HLD/LLD), architectural blueprints, and vendor proposals, ensuring system feasibility and seamless cross-platform integration.
 </li>
 <li>
 Define and document data flows across systems &mdash; from IoT sensors and gateways through to DCIM/BMS, CCTV/VMS, analytics engines, and command &amp; control dashboards.
 </li>
 <li>
 Act as the technical bridge from initial design discussions through to final delivery, working closely with project managers, business analysts, architects, developers, and external partners.
 </li>
 <li>
 Coordinate with the PMO and product managers to assess resource requirements, delivery goals, and potential risks; identify risks and implement mitigation strategies to minimize impact on project quality and timelines.
 </li>
 <li>
 Oversee system integration testing (SIT), UAT, and commissioning activities, validating that delivered solutions meet performance, security, and regulatory requirements.
 </li>
 <li>
 Prepare and maintain high-quality technical documentation including architecture documents, integration diagrams, data flow diagrams, test plans, SOPs, and acceptance criteria.
 </li>
 <li>
 Provide cost modelling and technical inputs for financial forecasts, including BoMs, CAPEX/OPEX estimates, and TCO projections based on solution design.
 </li>
 <li>
 Support value engineering and scenario analysis, ensuring architecture decisions are cost-optimized, risk-aware, and aligned with budget and business case objectives.
 </li>
 <li>
 Ensure compliance with industry standards and regulations for security systems and drive adherence to security, compliance, and performance best practices, while considering long-term scalability.
 </li>
 <li>
 Cultivate a supportive team environment by valuing input from team members, mentoring junior engineers, and encouraging professional growth.
 </li>
 </ul>
 
 
 Qualifications
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in engineering, Computer Science, Information Technology, or a related field.
 </li>
 <li>
 10+ years of experience in system engineering, solution architecture, or technical lead roles within smart infrastructure, data centre, or mission-critical environments.
 </li>
 <li>
 Proven experience with OT systems integration &mdash; BMS, DCIM, SCADA, CCTV/VMS, PSIM, access control, and fire alarm systems.
 </li>
 <li>
 Strong understanding of OT/IoT protocols such as BACnet, Modbus, MQTT, and REST/HTTP APIs.
 </li>
 <li>
 Hands-on experience with multi-vendor platform integrations involving AI platforms, video management systems, connectivity, and IoT sensors.
 </li>
 <li>
 Strong understanding of edge vs. cloud-based architectures, including deployment trade-offs and performance considerations.
 </li>
 <li>
 Solid understanding of data centre concepts &mdash; power, cooling, racks, DCIM/BMS, monitoring, incident and change management.
 </li>
 <li>
 Experience with Agile/Scrum delivery practices, including backlog management and sprint planning.
 </li>
 <li>
 Exceptional interpersonal, stakeholder management, and client-facing skills, with a collaborative and empathetic approach.
 </li>
 <li>
 Strong organizational, planning, and problem-solving skills, with attention to detail and a proactive mindset.
 </li>
 <li>
 Excellent communication and documentation skills with the ability to translate complex technical concepts into business-friendly language.
 </li>
 </ul>
 
 
 Preferred Experience
 
 
 <ul>
 <li>
 Experience in mission-critical facilities &mdash; data centres, critical infrastructure, smart buildings, or industrial IoT environments.
 </li>
 <li>
 Exposure to digital twin platforms, 3D modelling, or BIM-based systems.
 </li>
 <li>
 Experience with AI/ML and analytics use cases for operations, security, and automation.
 </li>
 <li>
 Familiarity with cloud-native IoT platforms (e.g., Azure IoT, Kafka) and enterprise system integration.
 </li>
 <li>
 Background in system integrator firms or large-scale infrastructure delivery programmes.
 </li>
 </ul>
 
 
 
 
 Join us at Presight, where we offer a culture of innovation, outstanding career growth opportunities, and competitive rewards. If you're eager to conquer new frontiers in AI and thrive in a dynamic environment, we welcome you to our community.
 
 
 
 
 
 
 What Working at Presight Offers
 
 
 <ul>
 <li>
 
 Culture:
 
 An open, diverse and inclusive environment with a global vision that encourages personal growth and focuses on ground-breaking, industry-first innovations.
 </li>
 <li>
 
 Career:
 
 Outstanding learning, development &amp; growth opportunities via structured training programmes and innovative, high-tech projects.
 </li>
 <li>
 
 Rewards:
 
 A competitive remuneration package with a host of perks including healthcare, education support, leave benefits and more.
 </li>
 </ul>
 
 
</div>

Lead Software Engineer

Antal International

<div>
 
 Antal International is collaborating with one of the UAEs leading government entities on a landmark initiative to modernize and strengthen the nation&rsquo;s financial infrastructure.
 
 
 
 
 
 This transformative program is driving the future of banking and financial services through
 
 AI, data analytics, and advanced digital technologies
 
 , including the development of next-generation AI-powered financial platforms.
 
 
 
 
 
 We are now looking to engage exceptional
 
 AI professionals (UAENationals and Expats)
 
 to be part of this high-impact transformation journey.
 
 
 
 
 
 
 
 ROLES IN DEMAND INCLUDE:
 
 
 
 <ul>
 <li>
 AI / Machine Learning Engineers
 </li>
 <li>
 AI/ ML Data Analyst
 </li>
 <li>
 Data Scientist (AI/ML Focus)
 </li>
 <li>
 Data Scientists &amp; Data Engineers
 </li>
 <li>
 AI Product &amp; Platform Specialists
 </li>
 <li>
 AI Digital Transformation Experts
 </li>
 <li>
 Analytics &amp; AI Strategy Professionals
 </li>
 </ul>
 
 
 
 
 
 
 KEY RESPONSIBILITIES
 
 
 
 <ul>
 <li>
 Design, develop, and deploy AI/ML models and data-driven solutions to solve complex business problems
 </li>
 <li>
 Work on end-to-end machine learning lifecycle including data collection, feature engineering, model training, evaluation, and deployment
 </li>
 <li>
 Build scalable data pipelines and support data engineering activities for structured and unstructured data
 </li>
 <li>
 Perform advanced data analysis to generate actionable insights for business and technology stakeholders
 </li>
 <li>
 Collaborate with product teams to integrate AI capabilities into digital platforms and applications
 </li>
 <li>
 Support AI-driven digital transformation initiatives across business functions
 </li>
 <li>
 Develop dashboards, analytics frameworks, and reporting systems for decision-making
 </li>
 <li>
 Contribute to AI strategy, experimentation, and innovation initiatives
 </li>
 <li>
 Ensure model performance, optimization, and continuous improvement in production environments
 </li>
 <li>
 Work closely with cross-functional teams including product, engineering, and business stakeholders
 </li>
 </ul>
 
 
 
 
 
 
 REQUIRED SKILLS &amp; QUALIFICATIONS
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Data Science, AI, Engineering, Mathematics, or related field
 </li>
 <li>
 Strong understanding of
 
 AI, Machine Learning, and Data Analytics concepts
 
 </li>
 <li>
 Experience with Python, SQL, and data processing frameworks
 </li>
 <li>
 Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
 </li>
 <li>
 Knowledge of data engineering tools and cloud platforms (AWS, Azure, or GCP)
 </li>
 <li>
 Experience in building dashboards and analytical models is an advantage
 </li>
 <li>
 Strong problem-solving, analytical, and communication skills
 </li>
 <li>
 Ability to work in fast-paced, agile, and transformation-driven environments
 </li>
 </ul>
 
 
 
 
 
 
 WHAT YOU&rsquo;LL WORK ON
 
 
 
 <ul>
 <li>
 Building and deploying AI/ML models and intelligent systems
 </li>
 <li>
 Developing scalable data pipelines and analytics solutions
 </li>
 <li>
 Driving AI-powered digital transformation initiatives
 </li>
 <li>
 Collaborating with product, engineering, and business teams
 </li>
 <li>
 Delivering insights and solutions that impact real business outcomes
 </li>
 </ul>
 
 
</div>

AI, Data & Digital Transformation Professionals (UAEN & Expats)

Solomon People Solutions

<ul><li>Freelance AI Trainer for Business Leader- ONLY TRAINERS APPLY with CV and Photograph</li></ul>ARTIFICIAL INTELLIGENCE FOR BUSINESS LEADERS TRAINING COURSE Course Overview Artificial intelligence is no longer just for tech giants. Companies across every industry, from finance and healthcare to retail and logistics, are using AI to drive efficiency, improve decision-making, and create new opportunities. But successful AI adoption requires more than just investment in technology; it demands strong leadership, informed decision-making, and a clear vision. This course establishes a connection between AI technology and business strategy. You&rsquo;ll explore the fundamentals of machine learning, natural language processing, and automation, all from a leader&rsquo;s perspective. Through case studies and hands-on exercises, you&rsquo;ll discover how to assess AI opportunities, manage risks, and build AI-driven initiatives that deliver measurable resultsLearning Objectives :This course gives you the knowledge to lead AI-driven initiatives with confidence. &bull; Understand the core concepts of AI and machine learning &bull; Identify high-impact AI applications for business growth &bull; Assess the risks and ethical considerations of AI adoption &bull; Develop an AI implementation strategy aligned with your goals &bull; Work effectively with data scientists and AI teams &bull; Measure the success of AI-driven initiatives &bull; Leverage AI for automation, customer insights, and operational efficiency &bull; Navigate the legal and regulatory landscape of AIThis course helps businesses: Identify AI opportunities that drive revenue and efficiency &bull; Reduce costs by automating repetitive tasks &bull; Improve customer experience through AI-driven insights &bull; Strengthen risk management with predictive analytics &bull; Enhance data-driven decision-making across departments &bull; Ensure responsible AI adoption with ethical considerations &bull; Foster an AI-ready culture within the organizationTraining Methodology This is not a technical coding course&mdash;it&rsquo;s a hands-on, business-focused AI training designed for leaders. You&rsquo;ll learn through: Case studies showing AI&rsquo;s impact across industries Interactive discussions on AI strategy and risk management Group exercises to explore AI implementation challenges Live demonstrations of AI-powered tools in action Workshops on developing an AI roadmap for your business Expert insights from professionals working in AI strategyCourse OutlineMODULE 1: UNDERSTANDING AI AND ITS BUSINESS IMPACT: AI vs. traditional automation: What&rsquo;s the difference? Key AI technologies: Machine learning, NLP, and computer vision AI&rsquo;s role in decision-making and competitive advantage Myths and misconceptions about AI How AI is reshaping industries worldwideMODULE 2: AI STRATEGY FOR BUSINESS LEADERS: Identifying AI opportunities in your organization Building an AI-ready culture within teams Managing AI projects without a technical background Aligning AI initiatives with business objectives Avoiding common AI adoption pitfallsMODULE 3: AI-DRIVEN AUTOMATION AND EFFICIENCY: Streamlining operations with AI-powered automation AI for supply chain and logistics optimization Enhancing customer service with AI chatbots Predictive maintenance and operational forecasting Case studies of automation success storiesMODULE 4: AI AND DATA-DRIVEN DECISION-MAKING: How AI extracts insights from large datasets Understanding AI-powered predictive analytics Using AI for personalized customer experiences AI&rsquo;s role in fraud detection and risk assessment Leveraging AI for smarter marketing and sales strategiesMODULE 5: THE ETHICS AND RISKS OF AI ADOPTION: Bias in AI algorithms: Identifying and mitigating risks Privacy concerns and data security in AI applications The legal and regulatory landscape of AI AI and workforce transformation: Job displacement vs. augmentation Responsible AI development: Balancing innovation and ethicsMODULE 6: WORKING WITH AI TEAMS AND STAKEHOLDERS: Communicating AI projects to non-technical teams Collaborating with data scientists and engineers Managing AI project timelines and expectations Budgeting for AI investments Measuring AI success and ROIMODULE 7: AI IN MARKETING AND CUSTOMER ENGAGEMENT: Personalization at scale: AI-powered recommendations Sentiment analysis and brand monitoring with AI Chatbots and virtual assistants for customer support AI-driven content generation and advertising Data-driven customer segmentation with machine learningMODULE 8: AI IN FINANCIAL AND RISK MANAGEMENT: Predictive analytics for financial forecasting AI-powered fraud detection and compliance monitoring Algorithmic trading and investment strategies Risk assessment and credit scoring with AI AI&rsquo;s impact on financial regulations and auditsMODULE 9: EMERGING AI TRENDS AND FUTURE OPPORTUNITIES: The rise of generative AI and deep learning applications AI-powered robotics and autonomous systems The intersection of AI and IoT (Internet of Things) AI for sustainability and environmental impact Preparing for the next wave of AI advancementsMODULE 10: BUILDING YOUR AI ROADMAP: Conducting an AI readiness assessment for your organization, Defining key AI initiatives and success metrics Creating a phased AI adoption plan Identifying quick wins and long-term AI investments Gaining stakeholder buy-in for AI projectsJob Types: Part-time, Temporary, ContractPay: AED50.00 per hour

TRAINER ON AI FOR BUSINESS LEADERS

Group AMANA

<div>
 
 Amana is seeking an experienced Data Platform Lead with deep expertise in Databricks, the Microsoft Azure ecosystem, and modern lakehouse architectures. The ideal candidate will play a central role in Amana's ongoing platform refresh, moving workloads from Synapse Analytics to a Databricks lakehouse with Unity Catalog, and building the technical foundation that powers analytics, AI, and governance across the enterprise. This role sits within Amana's Data Science, Governance &amp; AI Centre of Excellence, working alongside architects, engineers, analysts, data scientists, and AI engineers, with future growth opportunities into senior platform leadership.
 
 
 
 
 
 
 Why This Role Matters
 
 
 
 Amana operates across capital-intensive sectors where data reliability, cost discipline, and speed of insight are business-critical. The enterprise data platform is the backbone of every downstream analytics, AI, and governance initiative &mdash; from ERP-integrated reporting and predictive models to Agentic AI and Copilot rollouts across the group.
 
 
 You will be at the technical centre of this transformation, designing, building, and hardening the lakehouse that the rest of the function depends on.
 
 
 
 
 
 
 Core Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Delivery
 
 
 <ul>
 <li>
 Design and deliver end-to-end Databricks lakehouse components &mdash; ingestion, transformation, semantic layer, and serving.
 </li>
 <li>
 Set and enforce Delta Lake and medallion architecture standards across bronze, silver, and gold layers.
 </li>
 <li>
 Lead the technical execution of the Synapse Analytics to Databricks migration, including parallel run, cutover, and decommissioning.
 </li>
 <li>
 Contribute to and sign off on reference designs, integration patterns, and architecture decision records.
 </li>
 </ul>
 
 
 
 
 
 Data Engineering &amp; Integration
 
 
 <ul>
 <li>
 Build and maintain robust ingestion and transformation pipelines from Amana's core enterprise systems: Oracle Fusion (Finance, HCM, P2P, CRM), Hyperion, CMiC, project and operations systems, SharePoint, and Power Platform.
 </li>
 <li>
 Apply strong CI/CD, DataOps, and infrastructure-as-code practices using Git, Azure DevOps, and Terraform or Bicep.
 </li>
 <li>
 Ensure platform reliability through monitoring, alerting, and structured incident response.
 </li>
 </ul>
 
 
 
 
 
 AI/ML &amp; Analytics Enablement
 
 
 <ul>
 <li>
 Build and operate feature store, MLOps, and LLMOps foundations on Databricks.
 </li>
 <li>
 Enable production-grade RAG, agent, and Copilot patterns in partnership with the Data Scientist and AI Engineer.
 </li>
 <li>
 Deliver Power BI semantic models, certified datasets, and self-service guardrails supporting the Amana Digital Academy and enterprise adoption.
 </li>
 </ul>
 
 
 
 
 
 Data Governance &amp; Trustworthy Data
 
 
 <ul>
 <li>
 Implement lineage, cataloguing, access control, data quality, and PDPL controls inside the platform using Unity Catalog and Microsoft Purview.
 </li>
 <li>
 Partner with the Data Governance Office to translate live policies into enforceable platform controls.
 </li>
 <li>
 Support regulatory, ethical, and internal compliance obligations across the data estate.
 </li>
 </ul>
 
 
 
 
 
 Cloud &amp; Cost Discipline
 
 
 <ul>
 <li>
 Own FinOps hygiene on the platform: cluster policies, workload tiering, rightsizing, and chargeback readiness.
 </li>
 <li>
 Translate cloud cost outcomes into commercial terms understood by finance and business stakeholders.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Technical Leadership
 
 
 <ul>
 <li>
 Work closely with the Data Architect, Data Engineer, Data Analyst, Data Scientist, and AI Engineer to set and uphold technical standards.
 </li>
 <li>
 Provide hands-on technical guidance and code review across the team.
 </li>
 <li>
 Translate business requirements into technical designs with clear delivery outcomes.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 <ul>
 <li>
 Minimum of 7 years in data engineering or data platform work, with strong hands-on delivery experience.
 </li>
 <li>
 At least 3 years hands-on with Databricks, Apache Spark, and Delta Lake at enterprise scale. Snowflake or BigQuery experience is acceptable where the CV shows a real Databricks migration.
 </li>
 <li>
 Contributed to the build or rebuild of an enterprise data platform serving multiple business domains.
 </li>
 <li>
 Deep hands-on experience with the Azure data stack: Databricks, ADLS, Azure Data Factory, Synapse, Azure SQL, Fabric.
 </li>
 <li>
 Direct experience integrating heavy ERP sources: Oracle Fusion, Hyperion, CMiC, or equivalent estates.
 </li>
 <li>
 Governance shipped to production using Unity Catalog or Microsoft Purview, with PDPL or GDPR controls operational, not theoretical.
 </li>
 <li>
 Practical FinOps outcomes on cloud spend.
 </li>
 <li>
 Strong on CI/CD, Git, Azure DevOps, and infrastructure-as-code (Terraform or Bicep).
 </li>
 <li>
 Excellent written and verbal communication skills across technical and business audiences.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Direct experience of a Synapse Analytics to Databricks migration.
 </li>
 <li>
 Exposure to MLOps and LLMOps stacks: MLflow, feature store, vector stores, RAG, agent frameworks.
 </li>
 <li>
 Familiarity with Power BI semantic models and enterprise BI governance.
 </li>
 <li>
 Streaming and event-driven experience: Kafka, Event Hubs, Structured Streaming.
 </li>
 <li>
 Multi-entity, multi-country group exposure with mixed data residency considerations.
 </li>
 <li>
 Industry experience in construction, engineering services, manufacturing, energy, or logistics.
 </li>
 </ul>
 
 
 
 
 
 Certifications
 
 
 
 
 
 Mandatory:
 
 
 
 <ul>
 <li>
 
 Databricks Certified Data Engineer Professional
 
 (Candidates holding the Associate level will be considered on the condition that Professional is achieved within 6 months of joining.)
 </li>
 </ul>
 
 
 Preferred (one or more):
 
 
 <ul>
 <li>
 
 Databricks Certified Machine Learning Professional
 
 </li>
 <li>
 
 Databricks Certified Generative AI Engineer Associate
 
 </li>
 <li>
 
 Microsoft Certified: Azure Data Engineer Associate
 
 (DP-203 / DP-700)
 </li>
 <li>
 
 Microsoft Certified: Fabric Analytics Engineer Associate
 
 (DP-600)
 </li>
 <li>
 
 Microsoft Certified: Azure Solutions Architect Expert
 
 </li>
 <li>
 
 Certified Data Management Professional (CDMP)
 
 &mdash; DAMA
 </li>
 </ul>
 
 
 Education
 
 
 
 M.Tech / B.E. / B.Tech (Computer Science, Information Systems, IT) / MCA / MCS.
 
</div>

Data Platform Lead

Delivery Hero

<div>Company Description 
Since launching in Kuwait in 2004, talabat has become the region&rsquo;s leading on-demand delivery app, serving millions of customers across eight countries. Our Quick Commerce (QC) Hub powers the grocery and convenience delivery experience &mdash; getting everyday essentials to customers&rsquo; doors in minutes, not hours.
Behind every delivery is data. Our QC data team works at a scale most data scientists only read about: millions of daily transactions, thousands of partners, and decisions that directly shape how people across the Middle East get their groceries delivered. We&rsquo;re building an analytics-first culture where every product and business decision is grounded in evidence. 
Job Description 
Why This Role
As a Data Scientist on the QC Hub team, you&rsquo;ll be the analytical brain behind one of talabat&rsquo;s fastest-growing verticals. You won&rsquo;t just crunch numbers &mdash; you&rsquo;ll partner directly with product and business leaders to shape strategy, design experiments that affect millions of users, and build the data foundations that power smarter decisions.
This is a role for someone who loves turning messy, ambiguous business questions into clean, actionable analysis &mdash; and who gets energy from seeing their insights change how a team operates.
What Success Looks Like<ul><li>
First 90 days: You&rsquo;ve ramped up on your domain, built relationships with your product and business partners, understood the data landscape, and delivered your first actionable analysis.</li><li>
By 6 months: You&rsquo;re the go-to analytical partner for your domain. You&rsquo;re independently designing and running experiments, and stakeholders regularly act on your recommendations.</li><li>
By 12 months: Your work has measurably improved decision quality in your domain. You&rsquo;ve built or refined data models that the team relies on daily, and you&rsquo;re mentoring newer team members on analytical best practices.</li></ul>
What You&rsquo;ll Actually Do
You&rsquo;ll spend roughly:<ul><li>
40% on deep analysis and experimentation &mdash; designing A/B tests, running multivariate experiments, doing deep dives into performance drivers, and turning findings into clear recommendations.</li><li>
30% on data modelling and quality &mdash; building and maintaining the data models that let us measure what matters, profiling source data, and ensuring data reliability.</li><li>
30% working with stakeholders &mdash; partnering with product and business managers to frame the right questions, set meaningful KPIs, and present insights that drive action.</li></ul>
Day-to-day, you&rsquo;ll:<ul><li>
Turn ambiguous business questions into structured analytical problems</li><li>
Build and maintain dimensional data models in BigQuery</li><li>
Design, execute, and interpret experiments (A/B and multivariate)</li><li>
Create automated dashboards and reports that stakeholders actually use</li><li>
Challenge assumptions with data &mdash; including your own</li><li>
Collaborate with data engineers on logging and data pipeline quality</li></ul>
You&rsquo;ll Thrive Here If You&hellip;<ul><li>
Love being embedded with business teams, not siloed in a data team</li><li>
Get satisfaction from changing how decisions are made, not just producing reports</li><li>
Are comfortable with ambiguity &mdash; many of your best projects will start as vague questions</li><li>
Care deeply about data quality and are willing to dig into source systems to understand what the data actually means</li><li>
Communicate clearly with non-technical stakeholders</li></ul>
This Might Not Be For You If You&hellip;<ul><li>
Want to build ML models full-time (this role is analytics and experimentation focused)</li><li>
Prefer working independently without regular stakeholder interaction</li><li>
Need clearly defined problems handed to you</li><li>
Are more interested in tools and techniques than business impact</li></ul> 

Qualifications 
What You Bring 
Education
Degree in a quantitative field (statistics, mathematics, economics, computer science, engineering, or similar) &mdash; or equivalent practical experience. A postgraduate degree is a plus but not required.
Must-Haves:<ul><li>
Strong SQL skills &mdash; you can write complex queries with window functions, CTEs, and optimise for performance on large datasets</li><li>
Reproducible analysis in Python or R &mdash; you write clean, well-structured analytical code, not one-off scripts</li><li>
Experiment design expertise &mdash; you understand when to use A/B vs. multivariate tests, can calculate sample sizes, and know the pitfalls of statistical testing</li><li>
Full analysis lifecycle experience &mdash; from problem framing through data auditing, analysis, interpretation, and presenting recommendations</li><li>
Data modelling knowledge &mdash; you understand dimensional design and can build models that serve both ad-hoc analysis and automated reporting</li><li>
Product analytics intuition &mdash; you&rsquo;re familiar with metrics like conversion, engagement, and retention, and know how to measure product health</li><li>
3+ years in data science, analytics, or a related quantitative field</li></ul>
Nice-to-Haves:<ul><li>
Experience with BigQuery and Google Cloud Platform</li><li>
Data engineering skills (Airflow, dbt, or similar pipeline tools)</li><li>
Experience with ML frameworks (Scikit-learn, XGBoost, LightGBM)</li><li>
Familiarity with modern data tools and AI-assisted analysis workflows</li><li>
Experience in an online consumer product or marketplace environment</li></ul> 

Additional Information 
What We Offer<ul><li>
Impact at scale &mdash; your work directly affects how millions of people get their daily essentials</li><li>
An analytics-first culture &mdash; a data team that&rsquo;s genuinely invested in analytical excellence, not just dashboarding</li><li>
Modern tooling &mdash; BigQuery, GCP ecosystem, and the freedom to experiment with new approaches including AI-assisted workflows</li><li>
Career growth &mdash; past data scientists on the team have grown into senior individual contributor roles and analytics leads</li><li>
Great Place to Work &mdash; talabat is a certified Great Place to Work across multiple countries in the region</li></ul></div>

Data Scientist II - Analysis, QC

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AI Data Scientists (CCTV Analytics)

AI Data Scientists (CCTV Analytics)

Lead Software Engineer

AI, Data & Digital Transformation Professionals (UAEN & Expats)

TRAINER ON AI FOR BUSINESS LEADERS

Data Platform Lead

Data Scientist II - Analysis, QC