Data Scientist Jobs

Job Description: About Revolut People deserve more from their money. More visibility, more control, and more freedom. Since 2015, Revolut has been on a mission to deliver just that. Our powerhouse of products — including spending, saving, investing, exchanging, travelling, and more — help our 75+ million customers get more from their money every day. As we continue our lightning-fast growth, 2 things are essential to our success: our people and our culture. In recognition of our outstanding employee experience, we've been certified as a Great Place to Work. So far, we have 13,000+ people working around the world, from our offices and remotely, to help us achieve our mission. And we're looking for more brilliant people. People who love building great products, redefining success, and turning the complexity of a chaotic world into the simplicity of a beautiful solution. About The Role Our Data Science team solves complex problems with smart, practical solutions and improves how customers experience Revolut. Our Deep Learning Engineers are at the forefront of GenAI and LLM integration, building transformative products that range from user-facing tools to advanced process optimisation. We're looking for a Deep Learning Engineer to work with the most advanced LLMs available, developing solutions that have a tangible impact on millions of customers worldwide. You'll collaborate cross-functionally with Product Owners, Software Engineers, Data Analysts, and Operations Managers to deliver automated, scalable solutions that elevate and revolutionise customer interaction. Up to break barriers and shape what's next for the future of Revolut’s AI-driven capabilities? Let's get in touch. What You’ll Be Doing Building AI-driven features from scratch, like personal assistants, chatbots, copilots, and more Developing user-focused and backend features using deep learning Delivering impactful, scalable, data-driven AI solutions Collaborating with Product, Engineering, and Data teams to solve deep learning challenges Integrating cutting-edge AI technologies to drive innovation at Revolut What You'll Need Experience in deep learning within natural language processing area and large language models A bachelor's degree in a STEM major (mathematics, computer science, engineering) Excellent knowledge of data science (Python, SQL) and production tools A deep understanding of probability and statistics fundamentals Big-picture thinking to correctly diagnose problems and productionise research Excellent communication and collaboration skills to partner with Product Owners and business heads Nice to have A master's or PhD in a quantitative discipline Solid experience with additional programming languages, such as Java, Scala, C++ Experience at a large tech company worth >$15B School/university Olympic medal competitions in physics, maths, economics, or programming Building a global financial super app isn’t enough. Our Revoluters are a priority, and that’s why in 2021 we launched our inaugural D&I Framework, designed to help us thrive and grow everyday. We're not just doing this because it's the right thing to do. We’re doing it because we know that seeking out diverse talent and creating an inclusive workplace is the way to create exceptional, innovative products and services for our customers. That’s why we encourage applications from people with diverse backgrounds and experiences to join this multicultural, hard-working team. Requirements #J-18808-Ljbffr

Revolut is offering a Data Scientist and Analyst Internship in its UAE hub for penultimate‑year students. Over 8–10 paid weeks, you will work on real projects, guided by mentors, and gain hands‑on experience in analytics, data science and ML tools.The programme supports relocation to the UAE, visa assistance and accommodation where applicable, with an expectation to be in the office about 3 days per week. Strong Python/SQL and English are required. #J-18808-Ljbffr

Job SnapshotSenior Data Scientist - AI and Machine LearningLocation: Dubai, United Arab EmiratesIndustry: InternetFunction: R and D-ScienceExperience: Minimum 5 years across data science, machine learning engineering, and generative AIJob Type: Full-timeSenior Data Scientist - AI and Machine Learning in Dubai, United Arab Emirates is an Internet opportunity for an experienced data science professional responsible for designing, building, deploying, and improving production-grade machine learning and generative AI systems. This hiring role is suited to candidates seeking a senior AI and machine learning job in Dubai with end-to-end ownership across problem formulation, feature engineering, model development, experimentation, MLOps, LLM applications, production monitoring, and data-driven product decision-making.Job DetailsCountry: United Arab EmiratesCity: DubaiIndustry: InternetFunction: R and D-ScienceSalary: 30000-45000 Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer. Gender: AnyCandidate Nationality: AnyJob Type: Full-timeRole ContextThe Senior Data Scientist works within talabat 's global AI hub to develop intelligent systems that improve decisions across consumer products and business operations. The role owns a defined domain from initial business problem discovery through data modeling, model training, deployment, serving, experimentation, and ongoing performance monitoring. This position combines advanced data science with significant engineering responsibility. The successful candidate will work closely with Product Managers, Business Managers, Data Scientists, Machine Learning Engineers, and Engineering teams to convert complex operational and customer problems into scalable AI solutions that deliver measurable business impact.Key ResponsibilitiesTranslate ambiguous business challenges into clearly defined machine learning and data science problems with measurable success criteria.Identify high-impact opportunities where machine learning, generative AI, or advanced analytics can improve product and business outcomes.Design and build end-to-end machine learning systems suitable for production environments.Develop reliable data pipelines supporting feature creation, model training, evaluation, deployment, and monitoring.Perform feature engineering using large-scale behavioral, transactional, and product , evaluate, compare, and improve machine learning models using appropriate algorithms and architectures.Select practical modeling approaches based on business value, scalability, interpretability, performance, and operational complexity.Build production-grade code for machine learning applications and supporting services.Deploy trained models into production and maintain dependable model-serving workflows.Monitor model performance, data quality, drift, reliability, and downstream business impact after deployment.Apply generative AI and large language models to data enrichment, smart content understanding, automation, and decision-support use cases.Evaluate LLM approaches and determine when fine-tuning, prompting, retrieval, or traditional machine learning provides the most appropriate solution.Build and maintain data models and reusable features supporting model development.Develop automated analytical reporting that provides actionable insights for business and product stakeholders.Conduct systematic data profiling to understand source data, quality issues, generating systems, and behavioral closely with Engineering teams to understand instrumentation, event generation, and data dependencies.Design A-B tests and multivariate experiments to measure product and model impact.Analyze experiment results using appropriate statistical methods and translate findings into clear inferential, causal, predictive, and descriptive techniques according to the problem being solved.Partner with Product teams to understand user behavior, conversion, engagement, retention, and other product health with business stakeholders to convert analytical insights into practical actions and strategic decisions.Develop scalable recommendation, NLP, deep learning, pattern recognition, or predictive modeling solutions where Python and SQL extensively for reproducible analysis, modeling, validation, and production workflows.Build and orchestrate training and data workflows using platforms such as Airflow.Contribute to stronger MLOps practices covering repeatability, deployment, observability, testing, monitoring, and model lifecycle management.Improve internal machine learning tools, development practices, and engineering standards.Mentor other Data Scientists and support their technical development.Share machine learning knowledge through internal training, documentation, technical discussions, and practical coaching.Challenge unnecessary complexity and favor simpler solutions when they can deliver equal or stronger business outcomes.Maintain full ownership of assigned machine learning initiatives from discovery through measurable production impact.Ideal ProfileThe preferred candidate has at least 5 years of professional experience spanning data science, machine learning engineering, generative AI, or closely related technical disciplines, with demonstrated experience deploying machine learning models into production.A bachelor 's degree in engineering, computer science, technology, or a related field is required.A postgraduate qualification would be advantageous but is not essential.Deep technical expertise should include machine learning, deep learning, generative AI, NLP, recommendation systems, pattern recognition, and data mining.Candidates should have strong hands-on experience with relevant frameworks such as Scikit-learn, XGBoost, LightGBM, CatBoost, Keras, TensorFlow, PyTorch, Transformers, and LLM development techniques.Strong software engineering fundamentals are important.The successful candidate should be comfortable with data structures, algorithms, system design, ML system architecture, clean production code, and designing reliable services rather than limiting work to notebook-based analysis.Advanced Python and SQL capabilities are required, together with practical experience building data and machine learning pipelines.Exposure to Airflow, BigQuery, Google Cloud Platform, dimensional modeling, and feature engineering will be valuable.The position also requires strong statistical foundations covering experimentation, inferential methods, causal analysis, predictive modeling, and rigorous interpretation of results.Candidates should demonstrate ownership, curiosity, practical problem solving, strong collaboration, and clear developing machine learning systems for online consumer products would be especially relevant.Skills SetMachine learningGenerative AIArtificial intelligenceLarge language modelsLLM fine-tuningNatural language processingDeep learningRecommendation systemsPattern recognitionData miningPythonSQLScikit-learnXGBoostLightGBMCatBoostSupport Vector MachinesKerasTensorFlowPyTorchTransformersFeature engineeringData pipelinesTraining pipelinesAirflowMLOpsModel deploymentModel servingModel monitoringModel evaluationML system designSoftware engineeringData structuresAlgorithmsSystem designProduction machine learningA-B testingMultivariate testingExperiment designStatistical analysisCausal analysisPredictive modelingInferential statisticsData modelingDimensional modelingProduct analyticsConversion analysisEngagement analysisRetention analysisBigQueryGoogle Cloud PlatformData profilingAutomated reportingTechnical mentoringWhy Join UsThis opportunity places the successful candidate within a high-impact AI environment where machine learning systems can influence millions of customer interactions and large-scale business decisions across talabat 's regional platform. The role provides substantial ownership over the complete ML lifecycle rather than separating modeling, engineering, deployment, and measurement into isolated responsibilities. Working within the global AI hub also offers exposure to complex consumer data, generative AI applications, recommendation systems, experimentation, production MLOps, and scalable decision systems. For an experienced Data Scientist, the position provides room to deepen technical leadership while mentoring colleagues and shaping how advanced AI is applied across one of the region 's largest digital commerce ecosystems.About the Companytalabat is a leading on-demand food, grocery, and Q-commerce technology platform operating across the Middle East. The company uses data, artificial intelligence, logistics technology, and digital commerce systems to connect customers with restaurants and local retailers while supporting riders and partners across multiple regional markets. #J-18808-Ljbffr

Sana Commerce in Dubai is seeking a senior Data Engineer to design and maintain data pipelines optimized for ML/AI workloads, handling large-scale unstructured data and building feature stores.You will collaborate with data scientists and ML engineers to ensure data quality, governance, and scalable processing with Spark, Databricks, and Azure Data services. This hybrid role offers opportunities to shape data infrastructure across the organization. #J-18808-Ljbffr

We empower businesses in the digital economy and we know that every payment counts. Our Payment Performance teams mission is to manage and optimise merchants payment flow to achieve optimal conversion compliance and cost. is looking for a Data Analytics Manager to join our Payment Success team to craft an all-encompassing payments strategy tailored specifically for our Tier-1 merchants. You will be the main point of contact for a merchant regarding their payment performance. You will play a critical role in defining delivering and building tools for the right insights to showcase the value of our optimal payment strategies. You will work closely with Payment Performance engineers and data scientists leveraging cutting‑edge technology and data insights. You will also collaborate regularly with other teams and cross‑functional stakeholders to establish priorities and drive merchant performance improvements. What youll be doing: Deliver expertise and guidance to our key merchants by crafting optimal payments strategy. Conduct deep-dive exploratory data analysis to uncover insights and anomalies Conduct experiments and A/B tests to improve performance including ML based solutions. Develop cutting‑edge automation tools aimed at monitoring and optimising merchants performance. Implement robust measurements to assess how proposed solutions impact merchants performance and revenue providing valuable insights for both internal and external ROI. Collaborate with various teams across the company to ensure an outstanding merchant experience and feed requirements for product development Elevate internal awareness particularly within the executive team regarding the full spectrum of merchant services and benefits provided Drive a culture of cross-team learning and knowledge sharing Qualifications : 5 years experience as data scientist working with large and diversified data sets Payments experience is mandatory for this role Bachelors degree preferably in Mathematics / Statistics / Computer Science / Engineering Finance or equivalent SQL/ Python knowledge to extract & analyse data from our Data Warehouse Experience with Git & Spark Databricks Retool API Ability to find creative and effective solutions for business problems Flexible adaptable and has a willingness to learn Additional Information : We believe in equal opportunities We work as one team. Wherever you come from. However you identify. And whichever payment method you use. Our clients come from all over the world and so do we. Hiring hard‑working people and giving them a community to thrive in is critical to our success. When you join our team well empower you to unlock your potential so you can do your best work. Wed love to hear how you think you could make a difference here with us. We want to set you up for success and make our process as accessible as possible. So let us know in your application or tell your recruiter directly if you need anything to make your experience or working environment more comfortable. Well be happy to support you. Take a peek inside life at via Our Culture video careers page LinkedIn Life pages Instagram Work : No Employment Type : Full-time •

We empower businesses in the digital economy and we know that every payment counts. Our Payment Performance teams mission is to manage and optimise merchants payment flow to achieve optimal conversion compliance and cost. is looking for a Data Analytics Manager to join our Payment Success team to craft an all-encompassing payments strategy tailored specifically for our Tier-1 merchants. You will be the main point of contact for a merchant regarding their payment performance. You will play a critical role in defining delivering and building tools for the right insights to showcase the value of our optimal payment strategies. You will work closely with Payment Performance engineers and data scientists leveraging cutting‑edge technology and data insights. You will also collaborate regularly with other teams and cross‑functional stakeholders to establish priorities and drive merchant performance improvements. What youll be doing: Deliver expertise and guidance to our key merchants by crafting optimal payments strategy. Conduct deep-dive exploratory data analysis to uncover insights and anomalies Conduct experiments and A/B tests to improve performance including ML based solutions. Develop cutting‑edge automation tools aimed at monitoring and optimising merchants performance. Implement robust measurements to assess how proposed solutions impact merchants performance and revenue providing valuable insights for both internal and external ROI. Collaborate with various teams across the company to ensure an outstanding merchant experience and feed requirements for product development Elevate internal awareness particularly within the executive team regarding the full spectrum of merchant services and benefits provided Drive a culture of cross-team learning and knowledge sharing Qualifications : 5 years experience as data scientist working with large and diversified data sets Payments experience is mandatory for this role Bachelors degree preferably in Mathematics / Statistics / Computer Science / Engineering Finance or equivalent SQL/ Python knowledge to extract & analyse data from our Data Warehouse Experience with Git & Spark Databricks Retool API Ability to find creative and effective solutions for business problems Flexible adaptable and has a willingness to learn Additional Information : We believe in equal opportunities We work as one team. Wherever you come from. However you identify. And whichever payment method you use. Our clients come from all over the world and so do we. Hiring hard‑working people and giving them a community to thrive in is critical to our success. When you join our team well empower you to unlock your potential so you can do your best work. Wed love to hear how you think you could make a difference here with us. We want to set you up for success and make our process as accessible as possible. So let us know in your application or tell your recruiter directly if you need anything to make your experience or working environment more comfortable. Well be happy to support you. Take a peek inside life at via Our Culture video careers page LinkedIn Life pages Instagram Work : No Employment Type : Full-time •

Cobblestone Energy in Dubai, UAE, is seeking a Junior Data Scientist to join our Commercial Analytics team. You will collect, clean, and model large market data, build predictive workflows, and push data-driven trading ideas into production.The role requires strong Python/R skills, experience with Pandas/NumPy/SQL, and a proactive, English-speaking mindset. We sponsor visas, offer relocation support, and provide an Employee Share Scheme along with a clear path to growth in a fast-paced trading #J-18808-Ljbffr

Amazon launched the Generative AI Innovation Center (GenAIIC) in June 2023 to help AWS customers accelerate the use of generative AI to solve business and operational problems and promote innovation in their organization. This is a team of strategists data scientists engineers and solution architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.( generative-ai-innovation-center).We're looking for Data Scientists capable of using generative AI and other techniques to design evangelize and implement state-of-the-art solutions for never-before-solved problems. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments research new algorithms and find new ways of optimizing risk profitability and customer experience.Emirati national is required.Key job responsibilitiesAs a Data Scientist you willCollaborate with AI/ML scientists engineers and architects to Research design develop and evaluate cutting-edge generative AI algorithms to address real-world challengesInteract with customers directly to understand the business problem help and aid them in implementation of generative AI solutions deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to productionCreate and deliver best practice recommendations tutorials blog posts sample code and presentations adapted to technical business and executive stakeholderProvide customer and market feedback to Product and Engineering teams to help define product directionAbout the teamThe team helps customers imagine and scope the use cases that will create the greatest value for their businesses select and train or fine tune the right models define paths to navigate technical or business challenges develop proof-of-concepts and make plans for launching solutions at scale. The Generative AI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.Diverse ExperiencesAWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.Why AWSAmazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.Inclusive Team CultureHere at AWS its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences inspire us to never stop embracing our uniqueness.Mentorship & Career GrowthWe're continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life BalanceWe value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home theres nothing we cant achieve in the cloud.Bachelors degree Or Masters degree with several years of experienceSeveral years of experience building models for business applicationsExperience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing neural deep learning methods and/or machine learningExperience in using Python and hands on experience building models with deep learning frameworks like Tensorflow Keras PyTorch MXNetPhD or Masters degree in computer science engineering mathematics operations research or in a highly quantitative fieldPractical experience in solving complex problems in an applied environmentHands on experience building models with deep learning frameworks like PyTorch Tensorflow or JAXPrior experience in training and fine-tuning of Large Language Models (LLMs)Knowledge of AWS platform and toolsOur inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner. #J-18808-Ljbffr

SAP is seeking a senior data scientist to design, develop, and apply advanced data science, statistical, and ML methods to solve business problems. Embedded within customer environments and fast-moving delivery teams, you translate challenges into analytical solutions at speed and ensure data-driven outcomes that drive measurable value.You will work with customers to deliver production-ready analytics on SAP data landscapes, collaborate with cross-functional teams, and lead complex workstreams #J-18808-Ljbffr

SAP is seeking a senior data scientist to design, develop, and apply advanced data science, statistical, and ML methods to solve business problems. Embedded within customer environments and fast-moving delivery teams, you translate challenges into analytical solutions at speed and ensure data-driven outcomes that drive measurable value.You will work with customers to deliver production-ready analytics on SAP data landscapes, collaborate with cross-functional teams, and lead complex workstreams #J-18808-Ljbffr