Data Scientist Jobs

talabat seeks a Manager, Data Scientist - AI to lead a team delivering ML and generative AI systems powering product and business decisions. You will own roadmap, drive scalable AI initiatives, and ensure world‑class ML practices across data, models, and production monitoring.You will collaborate with product and engineering teams, advocate harness‑first thinking, and mentor talent while delivering measurable business value through Net AI Value Delivered. #J-18808-Ljbffr

Ethos is seeking a data-focused professional to help train a language model on professional documents, spreadsheets, and slide decks. You will create, evaluate, and refine AI-generated documents across core workflows and collaborate with cross-functional stakeholders.The role is fully remote, with flexible 5-20 hours per week, starting ASAP and compensated at $80/hour. Candidates should have 4+ years in relevant roles and excellent written communication. #J-18808-Ljbffr

Position Summary IT Excellence is seeking an experienced, highly technical, and accomplished Data Engineer with 3 to 5+ years of hands‐on data engineering, cloud data architecture, and ETL/ELT pipeline development experience to join our technology team on a full-time permanent basis in Dubai, UAE. In this specialized data engineering role, you will spearhead designing, building, and maintaining scalable and reliable data pipelines and cloud infrastructure to support advanced Data Science, GenAI applications, and enterprise analytical reporting. You will work closely with data scientists, LLM engineers, and product analysts to deliver robust, high‐performance data systems. Ideal candidates bring a robust academic degree in computer science or engineering, deep practical mastery of Azure data platforms (Azure Data Factory, Databricks, Synapse Analytics), PySpark, Python, and SQL, and immediate availability for deployment in Dubai. Detailed Job Description As a Data Engineer at IT Excellence in Dubai, UAE, you will take full ownership of end‐to‐end data pipeline development, cloud data lake modeling, workflow orchestration, and infrastructure automation. Your day‐to‐day responsibilities encompass designing and maintaining ETL/ELT pipelines using Azure Data Factory, Azure Databricks, PySpark, Scala, and SQL, building and optimizing data models in Azure Synapse Analytics, and deploying Apache Airflow pipelines on Red Hat Linux using Kubernetes. You will collaborate proactively with cross‐functional data science and analytics squads to implement data quality checks, validation rules, error handling, and comprehensive monitoring. Working in a fast‐paced technology consulting environment in Dubai, you will drive data reliability, pipeline scalability, and cloud cost optimization. Key Responsibilities Design, develop, and maintain robust ETL/ELT pipelines using Azure Data Factory, Azure Databricks, PySpark, Scala, and SQL. Build and optimize scalable data models and analytical tables using Azure Synapse Analytics and Azure Data Lake Storage Gen2. Build and deploy Apache Airflow pipeline orchestration workflows on Red Hat Linux environments using Kubernetes. Implement comprehensive data quality checks, schema validation, automated error handling, and pipeline monitoring. Manage Azure data platform components with an uncompromising focus on performance tuning, security, and cost optimization. Collaborate proactively with Data Scientists, LLM Engineers, and Product Analysts to deliver clean, accessible enterprise data. Develop real‐time and batch data ingestion solutions from external APIs, transactional databases, Azure Event Hubs, and Kafka. Optimize large‐scale data processing and storage using partitioning, indexing, Parquet, Delta Lake, and related technologies. Implement enterprise data governance, access control, and security best practices across all data stores. Troubleshoot complex pipeline and cloud platform issues to ensure high availability, reliability, and uptime. Automate infrastructure workflows and deployments using CI/CD pipelines and Infrastructure‐as‐Code tools (ARM, Bicep, Terraform). Required Qualifications & Skills Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, or a related technical discipline. Minimum 3 to 5+ years of hands‐on professional Data Engineering experience in enterprise cloud environments. Strong SQL skills and professional proficiency in Python or Scala programming. Strong hands‐on operational experience with Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage, and Azure Blob Storage. Extensive practical experience with Apache Spark, PySpark, or Scala distributed data processing frameworks. Strong understanding of enterprise data warehousing, data modeling principles, and ETL/ELT design patterns. Proven experience with data pipeline orchestration and scheduling tools (Apache Airflow). Familiarity with Git version control, CI/CD pipelines, Kubernetes, Linux environments, and data governance practices (Application email: [email protected]). Nice-to-Have Skills Professional certifications such as Microsoft Certified: Azure Data Engineer Associate or Databricks Certified Data Engineer. Hands‐on experience with streaming data platforms such as Apache Kafka or Azure Event Hubs. Prior working experience in tier‐1 enterprise technology consulting firms or data‐driven startups in the UAE / GCC region. Advanced performance tuning experience for Delta Lake storage formats. Bilingual proficiency in English and Arabic. Application Information Recruiter: IT Excellence Talent Acquisition Practice Contact Name: Harsh (Recruitment Lead) Email: [email protected] Phone: Unspecified Application URL: Unspecified Salary/Rate: Competitive market rate commensurate with experience Deadline: Open until filled Notice Period: Immediate to short notice preferred Contract Duration: Permanent / Full‐Time Onsite (Dubai, UAE) Recruitment Pro Tip When applying for senior data engineering roles in Dubai, ensure your resume explicitly highlights your Azure Databricks Spark depth, Airflow orchestration experience, and cloud cost optimization track record.

Job Purpose: As a Research Scientist specializing in Computer Vision your role will be crucial in advancing cutting-edge computer vision technologies and contributing to the development of intelligent systems. You will be responsible for a wide range of tasks encompassing research, development, and implementation of Computer Vision solutions, with a particular emphasis on Python coding, machine learning techniques, and deep learning methodologies. Key Responsibilities: • Lead the research of technology for improving efficiency in Computer Vision models while performing target capabilities or supporting many capabilities, such as novel architectures and improved pre-training. • Design and implement Computer Vision algorithms for model training and prediction, leverage ML infrastructure, and contribute to model optimization and data processing, using Pytorch or other frameworks. • Integrate and improve Computer Vision algorithms to work with other models such as LLMs • Identify defined problems/gaps in existing technology and engage other Research teams, stakeholders and leaders to expand efficient Computer Vision technology. • Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies. • Write up results in design documents, technical reports, and papers for publication. • Represent MBZUAI at industry conferences and events, showcasing the institution’s cutting-edge HPC and deep learning capabilities and establishing MBZUAI as a global leader in AI research and innovation. • Perform all other duties as reasonably directed by the line manager that are commensurate with these functional objectives. Academic Qualifications: Minimum: • Master’s in Computer Science, a related technical field, or equivalent practical experience. Preferred: • PhD or equivalent research experience in Computer Vision experience. Minimum Professional Experience: • Experience with state-of-the-art Gen AI techniques and models (e.g., LLMs, Multi-Modal, Large Vision Models) or with Gen AI-related concepts (e.g., language modeling, computer vision). • Knowledge of algorithms, including one or more of the following: imaging, computer vision, computer graphics, or parallel computation. • Experience with software development in one or more programming languages (e.g. Python, C++), and with data structures/algorithms. • Excellent problem-solving and troubleshooting skills to address complex technical challenges. • Effective communication and collaboration skills to work with cross functional teams. • Ability to effectively navigate ambiguity. Preferred Professional Experience: • Knowledge of modern deep learning techniques and Generative AI for photography. • Experience leading research efforts and influencing other researchers. • Experience with efficiency, modularity or related topics for LLMs. • Experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). • Experience with design and optimization of algorithms in performance constrained environments (e.g., mobile). • Experience in innovative research, contributing to research communities including publishing in forums (e.g., ACL, EMNLP, NAACL, EACL, COLING, ICLR, AAAI, NeurIPS).

Raw Ventures Global Limited in Dubai seeks a senior data scientist to own end-to-end data science: decide what to measure, acquire data, build models, and defend conclusions. You work directly with traders, deal economists, finance and treasury, and the founders—no account manager in between. This role covers P&L, cost and financial transactions with a data-driven approach; a small team of junior data scientists may report to you. #J-18808-Ljbffr

Binance.US is seeking a Senior Product Data Scientist to own and drive high-impact ML and data science projects. This role involves working independently on large problems to deliver findings that influence product strategy. The ideal candidate will manage end-to-end ML projects, build models for user segmentation, and conduct analyses on user behavior to identify growth opportunities. Strong business acumen and communication skills are essential. Work is fully remote, and a competitive salary range of AED42,000 - AED48,000 per month is offered. #J-18808-Ljbffr

About the opportunity About the Applied AI Tribe The Applied AI Tribe is talabat's internal AI engine, a team obsessed with turning cutting-edge AI into genuine, measurable business value. We don't build AI for its own sake. Our north star is Net AI Value Delivered. We have shipped 40+ AI products across four strategic streams: - Product & Tech Platform - AI capabilities embedded into talabat's core product and engineering platform. - Business Automations - streamlined workflows that save real time and money across operations. - Self-Serve AI Tools - empowering talabatis to build and use AI without needing to raise a ticket. - Training & Onboarding - upskilling the tribe so every team can participate in the AI era. Our engineering approach is built around shipping agentic AI systems at scale, with a harness-first philosophy, evaluation embedded into every product iteration, and production feedback loops that drive the roadmap. The Role As Manager, Data Scientist - AI within the Applied AI Tribe, you will lead a team of data scientists building and shipping the ML and generative AI systems that power decisions across talabat's product and business. You are equally a people leader and a technical practitioner, close enough to the work to make great technical decisions and grow your team, while owning the roadmap and delivery. Your team's work spans the full AI lifecycle: from framing ambiguous business problems through data modelling, feature engineering, model training, deployment, and production monitoring. A significant focus will be leveraging LLMs, agentic systems, and generative AI to automate decisions, enrich data, and build intelligent experiences at scale, all measured against Net AI Value Delivered. What's On Your Plate? People Leadership: - Lead, grow, and retain a team of data scientists, setting a high bar for technical quality, fostering a culture of ownership, and supporting each person's career development. - Partner with recruiting to attract top data science and ML talent as the tribe scales. - Mentor team members in ML best practices, agentic system design, production engineering, and stakeholder communication. - Run effective team rituals, planning, design reviews, retrospectives, that keep the team aligned and moving with pace. Technical Strategy & Delivery: - Translate ambiguous business problems into well-scoped ML and AI solutions with clear, measurable success criteria tied to the tribe's north star. - Own the team's technical roadmap: prioritise high-impact work across data enrichment, business automation, self-serve tooling, and agentic product features. - Champion harness-first thinking, ensure evaluation pipelines, LLM observability, tooling, and infrastructure are in place before agent logic is built on top. - Embed evaluation into every product iteration: golden datasets, stakeholder-aligned metrics, and weekly eval jobs that guide what gets built, fixed, or retired. - Oversee the full ML lifecycle: data pipelines, feature engineering, model training, production deployment, serving, and monitoring. - Drive adoption of LLMs and generative AI for data enrichment, smart content understanding, and automated decision-making at scale. - Design and analyse experiments (A/B and multivariate) to rigorously measure model and product impact. - Elevate ML and engineering standards across the team, improving MLOps, code quality, tooling, and internal learning programmes. Cross-functional Partnership: - Partner with product managers and business teams to identify high-value AI opportunities and shape them into the team's roadmap. - Communicate clearly with senior stakeholders, from problem framing through to results and recommendations. - Collaborate with engineering teams to understand data systems, build reliable data models, and ensure smooth production integration. What you need to be successful What Did We Order? Technical Experience - Deep expertise in machine learning, generative AI, deep learning, NLP, recommendation systems, and data mining. - Hands-on knowledge of ML and GenAI frameworks: Scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, Transformers, and LLM fine-tuning. - Proficiency with the OpenAI SDK and familiarity with major LLM provider APIs for building and orchestrating production AI systems. - Hands-on experience with LangGraph for building stateful, multi-step agentic workflows and complex agent orchestration patterns. - Experience with Hugging Face (Transformers, Hub, Inference API) for model sourcing, fine-tuning, and deployment. - Solid understanding of embeddings, dense and sparse retrieval, vector databases, and semantic search, for building RAG pipelines and similarity-based applications. - Strong software engineering fundamentals: clean production code, data structures and algorithms, ML system design. - Proven experience shipping and monitoring ML models in production, with a solid grasp of MLOps practices. - Strong data and ML engineering skills: building and orchestrating data pipelines (e.g., Airflow) and robust feature engineering. - Excellent SQL and Python; solid statistical foundations including experiment design, causal inference, and predictive methods. - Familiarity with agentic system design (harness-first thinking, LLM observability, evaluation pipelines, and production feedback loops) is a strong plus. - Experience with BigQuery and Google Cloud Platform is a plus. Qualifications - Bachelor's degree in Engineering, Computer Science, or a related field. A postgraduate degree is a plus. - 6+ years of experience in data science, ML engineering, and/or generative AI, including shipping models to production. - 2+ years managing or leading a data science or ML team, with a track record of developing talent and delivering through others. - Experience building ML systems in an online consumer product environment is a strong plus. Who we are Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region. We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily. Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner. What's in it for you Mindset & Ways of Working - Curiosity over certainty: you're excited to try the new model or framework this week. - Ownership: you treat cost, latency, and business impact as your problem, and your team's. - Bias to build: a prototype in a real workflow beats a perfect design doc every time. - Comfortable with ambiguity: most of what we build has no playbook yet, and you help write it. - Keep it simple: pick the approach that delivers the most value with the least complexity, and #makeithappen. At talabat, your success is defined by both results and behaviors. We hire for excellence in craft and for the Leadership Principles that shape how we think, decide, and collaborate. What you achieve matters, and how you achieve it defines us. Together, they move the business forward and deliver great experiences. Learn more about our Leadership Principles here.

Join one of the world's leading multi-strategy investment platforms as a Quant Researcher focused on Machine Learning and AI. This role sits within a highly successful systematic investment team that is investing heavily in next-generation research capabilities and the application of cutting-edge machine learning techniques to financial markets.The team is seeking exceptional researchers who can bring expertise from frontier AI, deep learning, large-scale modelling, and modern machine learning research into a fast-paced environment where ideas are rapidly tested and deployed. This is an opportunity to work on some of the most challenging prediction problems in the world while having direct impact on investment performance.ResponsibilitiesDevelop and implement machine learning models to identify predictive signals across global marketsResearch and apply state-of-the-art deep learning techniques for alpha generationDesign and test neural network architectures for financial forecasting and pattern recognitionWork with large, complex, and alternative datasets to uncover unique sources of investment insightConduct rigorous research, experimentation, and statistical validation of trading signalsCollaborate closely with Portfolio Managers, Quant Researchers, and Data ScientistsBuild scalable research infrastructure and production-ready modelling pipelinesStay at the forefront of developments in AI, machine learning, and quantitative researchContribute to the development of systematic investment strategies using modern ML techniquesRequirementsPhD or Master's degree in Machine Learning, Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative disciplineStrong background in machine learning research and modellingExperience building and deploying deep learning models in real-world environmentsExpertise in areas such as neural networks, representation learning, transformers, foundation models, reinforcement learning, probabilistic modelling, or large-scale optimisationExcellent programming skills in Python and familiarity with modern ML frameworks such as PyTorch or TensorFlowStrong mathematical and statistical foundationsDemonstrated ability to conduct independent research and solve complex problemsExperience from leading AI labs, deep technology companies, research institutions, or high-performance machine learning environments is highly desirablePreferred BackgroundsWe are particularly interested in candidates from:Leading AI research labsFrontier foundation model teamsDeep learning and applied AI organisationsResearch-focused technology companiesQuantitative research groupsHigh-performance computing and data science environmentsAcademic researchers with strong publication records in machine learning or artificial intelligenceWhat You'll GetOpportunity to apply cutting-edge AI research to real-world investment decisionsAccess to significant computational, data, and research resourcesHighly collaborative environment alongside world-class investors and researchersCompetitive compensation package with substantial upside potentialDirect impact on investment outcomes and business growthRelocation support to Dubai where applicableExposure to one of the most intellectually challenging applications of machine learningThis position is ideal for researchers who are passionate about solving difficult prediction problems, building innovative machine learning systems, and applying frontier AI techniques in a highly competitive and rewarding environment.

Manager Data Science - Operations Job Snapshot Role: Manager Data Science - Operations Location: Dubai, United Arab Emirates Industry: Automotive Function: Data Science Experience: Minimum 4-5 years Job Type: Full-time Position Overview Al-Futtaim is hiring a Manager Data Science - Operations to join its Digital Technology and Customer Experience team in Dubai, United Arab Emirates. The role will lead and deliver AI and data science initiatives focused on operational efficiency, advanced analytics, business decision-making, and measurable commercial outcomes. The position requires hands-on expertise in machine learning, predictive modelling, statistical analysis, forecasting, and modern data platforms, together with the ability to translate complex analytical findings into practical recommendations. Country: United Arab Emirates City: Dubai Industry: Automotive Function: Data Science Salary: Not disclosed Gender: No Preference Candidate Nationality: Not specified Job Type: Full-time What you will do • Deliver AI and data science use cases designed to improve operational performance across the business. • Build and implement predictive models covering price elasticity, residual value prediction, predictive maintenance, customer churn, and anomaly detection. • Develop KPI metrics and reporting systems using statistical process control and data visualization techniques. • Apply statistical analysis, hypothesis testing, and machine learning methods to identify patterns and generate actionable business insights. • Use forecasting, regression, classification, clustering, time series analysis, and anomaly detection techniques according to business requirements. • Partner with cross-functional teams and business stakeholders to translate complex analytical findings into clear and practical recommendations. • Lead and support data scientists in delivering high-quality analytics solutions within agreed timelines. • Communicate technical findings effectively to non-technical stakeholders and decision-makers. Required Skills and Experience • Minimum 4-5 years of experience in customer analytics, finance analytics, operations analytics, or data science. • Bachelor 's or master 's degree in Computer Science, Statistics, Data Science, or a related field. • Strong hands-on expertise in advanced statistics and machine learning. • Practical knowledge of time series analysis, forecasting, regression, classification, clustering, and anomaly detection. • Strong proficiency in Python and SQL. • Experience working with Databricks. • Knowledge of machine learning frameworks and libraries including scikit-learn, TensorFlow, and PyTorch. • Experience with ARIMA, SARIMA, and Prophet for forecasting applications. • Knowledge of Natural Language Processing techniques. • Proven experience delivering machine learning and advanced analytics solutions within a business environment. • Ability to work effectively across functions and manage multiple stakeholders. • Strong capability to convert data science outputs into practical business insights and recommendations. Data Science and Technology Expertise The role requires experience with data visualization tools and libraries including Matplotlib, Seaborn, Plotly, and Bokeh. Candidates should also have a good understanding of MLOps, Git, big data technologies such as Spark, and optimization techniques. Strong problem-solving, critical thinking, project management, and stakeholder management capabilities are important, together with the ability to explain sophisticated analytical concepts clearly to business audiences. About the Team The position sits within Al-Futtaim 's Digital Technology and Customer Experience team and works closely with operations, business, and technology stakeholders. The team applies data, advanced analytics, and AI to business challenges with the aim of improving operational efficiency and enabling stronger customer and commercial outcomes. About the Company Al-Futtaim is a privately held regional business headquartered in Dubai, with operations spanning automotive, financial services, real estate, retail, and health. Al-Futtaim Automotive operates across eight countries in the Middle East, Asia, and North Africa and represents a portfolio of more than 25 automotive brands. Its mobility capabilities cover passenger and commercial vehicles, industrial equipment, logistics, leasing, aftersales, and financial services.

Join one of the world's leading multi-strategy investment platforms as a Quant Researcher focused on Machine Learning and AI. This role sits within a highly successful systematic investment team that is investing heavily in next-generation research capabilities and the application of cutting-edge machine learning techniques to financial markets.The team is seeking exceptional researchers who can bring expertise from frontier AI, deep learning, large-scale modelling, and modern machine learning research into a fast-paced environment where ideas are rapidly tested and deployed. This is an opportunity to work on some of the most challenging prediction problems in the world while having direct impact on investment performance.ResponsibilitiesDevelop and implement machine learning models to identify predictive signals across global marketsResearch and apply state-of-the-art deep learning techniques for alpha generationDesign and test neural network architectures for financial forecasting and pattern recognitionWork with large, complex, and alternative datasets to uncover unique sources of investment insightConduct rigorous research, experimentation, and statistical validation of trading signalsCollaborate closely with Portfolio Managers, Quant Researchers, and Data ScientistsBuild scalable research infrastructure and production-ready modelling pipelinesStay at the forefront of developments in AI, machine learning, and quantitative researchContribute to the development of systematic investment strategies using modern ML techniquesRequirementsPhD or Master's degree in Machine Learning, Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative disciplineStrong background in machine learning research and modellingExperience building and deploying deep learning models in real-world environmentsExpertise in areas such as neural networks, representation learning, transformers, foundation models, reinforcement learning, probabilistic modelling, or large-scale optimisationExcellent programming skills in Python and familiarity with modern ML frameworks such as PyTorch or TensorFlowStrong mathematical and statistical foundationsDemonstrated ability to conduct independent research and solve complex problemsExperience from leading AI labs, deep technology companies, research institutions, or high-performance machine learning environments is highly desirablePreferred BackgroundsWe are particularly interested in candidates from:Leading AI research labsFrontier foundation model teamsDeep learning and applied AI organisationsResearch-focused technology companiesQuantitative research groupsHigh-performance computing and data science environmentsAcademic researchers with strong publication records in machine learning or artificial intelligenceWhat You'll GetOpportunity to apply cutting-edge AI research to real-world investment decisionsAccess to significant computational, data, and research resourcesHighly collaborative environment alongside world-class investors and researchersCompetitive compensation package with substantial upside potentialDirect impact on investment outcomes and business growthRelocation support to Dubai where applicableExposure to one of the most intellectually challenging applications of machine learningThis position is ideal for researchers who are passionate about solving difficult prediction problems, building innovative machine learning systems, and applying frontier AI techniques in a highly competitive and rewarding environment.