46 Researchers jobs in the United Arab Emirates

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Qemtex is looking for a dedicated Research and Development Laboratory Technician to join our R&D team in Dubai. The role involves preparing high-quality samples according to the formulas provided by our R&D chemists and conducting all necessary performance tests for the prepared powder samples.

• Prepare powder samples that meet the required standards based on the formulas written by R&D chemists.
• Perform color matching according to RAL, Pantone, and other custom color specifications.
• Operate lab equipment, including grinders, extruders, mixers, dry-blenders, bonding machines, and other characterization tools.
• Plan and coordinate with the maintenance team for preventive maintenance and lab equipment repair.
• Follow all safety guidelines and use personal protective equipment (PPE) consistently.
• Ensure compliance with environmental regulations and workplace safety standards.
• Inspect finished products for defects and ensure they meet quality standards for new formulas.
• Maintain detailed records of coatings, batches, and work orders.
• Document any deviations or issues related to standard procedures for all formulas.
• Coordinate with engineers, production and quality control technicians, painters, assemblers, and supervisors on projects.
• Communicate effectively regarding the status of R&D projects and any issues related to the designed formulas.
• Participate in training and development opportunities to continuously enhance skills.
• Analyze competitor samples and prepare detailed reports.
• Handle customer complaints by providing technical support to the quality control team.
• Perform COA analyses, long-term test analyses, and all powder-related analyses, such as particle size distribution (PSD).
• Conduct tests using differential scanning calorimeter (DSC), pill flow, and gel time measurements.
• Manage raw material studies, follow up on long-term tests, and prepare reports on raw materials.
• Write scale-up reports for new raw materials and critical formulas.

• Proven experience in a laboratory environment focused on research and development.
• Proficiency in operating laboratory equipment and performing sample performance tests.
• Strong organizational skills with attention to detail.
• Ability to collaborate effectively with cross-functional teams.
• Knowledge of safety and environmental regulations in a laboratory setting.

This role supports strategic and operational decision-making across departments. It combines strong business acumen with technical proficiency in tools like Excel, SQL, Python, and Power BI.

• Data collection, cleaning, and analysis from various systems.
• Maintenance of regular performance dashboards for occupancy, revenue, collections, and expenses.
• Generation of actionable insights and data visualizations to support leadership in key decisions.
• Assistance with forecasting and scenario planning (e.g., revenue trends, cost optimization).
• Ad hoc analysis and research on market trends, competitors, and benchmarks.
• Collaboration with teams (Finance, Legal, IT, etc.) to understand business needs and validate data.
• Identification of inconsistencies or inefficiencies in data or internal workflows, and proposal of improvements.
• Support for automation of recurring reports using Excel, BI tools, SQL queries, or Python scripts.

• Bachelor's degree in a STEM field, Finance, Economics, Statistics, Business Analytics, or a related discipline.
• 2-4 years of experience in a business or data analysis role, preferably within real estate or operational functions.
• Familiarity with UAE real estate regulations is an advantage.
• Proficiency in Microsoft Excel (advanced level), SQL, and Python for data handling and automation.
• Experience with BI tools such as Power BI (or similar platforms).
• Ability to build dashboards, analyze KPIs, and explain findings to non-technical stakeholders.

• Full-time employment offers the opportunity to work with a dynamic team and contribute to the company's success.
• Employment Type: Full-time.
• Job Function: Business Development and Investment Management.

The Director of Data Analysis is responsible for collecting, processing, and analysing real estate data from various sources, with the aim of providing accurate, data-driven insights that support strategic decision-making in the real estate sector in United Arab Emirates. The role focuses on enhancing market transparency, developing sector-wide performance indicators, and supporting policy formulation and investment planning based on data.

Responsibilities

• Collecting and analyzing real estate data from multiple sources
• Processing and cleaning data to ensure its accuracy, consistency, and readiness for analysis
• Analyzing real estate data to extract and update the real estate index, which enhances market transparency
• Preparing reports and dashboards to support strategic decision-making
• Developing sector performance indicators (e.g., price indices, supply and demand, occupancy rates, etc.)
• Supporting policy development and investment planning by providing data-driven recommendations
• Contributing to real estate market studies and identifying market trends to support and update strategic urban development plans
• Collaborating with government entities and investors to provide transparent and accurate insights into the real estate market

Requirements

• Bachelor's degree in Economics, Statistics, Business Administration, Data Analysis, or a related field.
• 5 years of experience in data analysis or market research, with knowledge of the real estate market.
• Certifications in data analysis or economics are not required but are preferred
• Certifications in Data Analysis, such as RICS or CF

We are seeking a detail-oriented and analytical professional to join our team as a Data Analyst . In this role, you will be responsible for collecting, analyzing, and presenting data related to financial performance, sales performance, and other areas of responsibility.

Effective Business Decisions Using Data Analysis

ID 257

Course: Effective Business Decisions Using Data Analysis

This interactive, applications-driven 5-day course will highlight the added value that data analytics can offer a professional as a decision support tool in management decision making. It will show the use of data analytics to support strategic initiatives; to inform on policy information; and to direct operational decision making. The course will emphasize applications of data analytics in management practice; focus on the valid interpretation of data analytics findings; and create a clearer understanding of how to integrate quantitative reasoning into management decision making. Exposure to the discipline of data analytics will ultimately promote greater confidence in the use of evidence-based information to support management decision making.

• Discussions on applications of data analytics in management
• The importance of data in data analytics
• Applying data analytical methods through worked examples
• Focusing on management interpretation of statistical evidence
• How to integrate statistical thinking into the work domain

• Explain the scope and structure of data analytics.
• Apply a cross-section of useful data analytics.
• Interpret meaningfully and critically assess statistical evidence.
• Identify relevant applications of data analytics in practice.

• Professionals in management support roles
• Analysts who typically encounter data/analytical information regularly in their work environment
• Those who seek to derive greater decision-making value from data analytics

This course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension, and retention of the information presented. The daily workshops will be highly interactive and participative. This involves regular discussion of applications as well as hands-on exposure to data analytics techniques using Microsoft Excel. Delegates are strongly encouraged to bring and analyse data from their own work domain. This adds greater relevancy to the content. Emphasis is also placed on the valid interpretation of statistical evidence in a management context.

• Day One: Setting the Statistical Scene in Management
  • Introduction; The quantitative landscape in management
  • Thinking statistically about applications in management (identifying KPIs)
  • The integrative elements of data analytics
  • Data: The raw material of data analytics (types, quality, and data preparation)
  • Exploratory data analysis using Excel (pivot tables)
  • Using summary tables and visual displays to profile sample data
• Day Two: Evidence-based Observational Decision Making
  • Numeric descriptors to profile numeric sample data
  • Central and non-central location measures
  • Quantifying dispersion in sample data
  • Examine the distribution of numeric measures (skewness and bimodal)
  • Exploring relationships between numeric descriptors
  • Breakdown analysis of numeric measures
• Day Three: Statistical Decision Making – Drawing Inferences from Sample Data
  • The foundations of statistical inference
  • Quantifying uncertainty in data – the normal probability distribution
  • The importance of sampling in inferential analysis
  • Sampling methods (random-based sampling techniques)
  • Understanding the sampling distribution concept
  • Confidence interval estimation
• Day Four: Statistical Decision Making – Drawing Inferences from Hypotheses Testing
  • The rationale of hypotheses testing
  • The hypothesis testing process and types of errors
  • Single population tests (tests for a single mean)
  • Two independent population tests of means
  • Matched pairs test scenarios
  • Comparing means across multiple populations
• Day Five: Predictive Decision Making - Statistical Modeling and Data Mining
  • Exploiting statistical relationships to build prediction-based models
  • Model building using regression analysis
  • Model building process – the rationale and evaluation of regression models
  • Data mining overview – its evolution
  • Descriptive data mining – applications in management
  • Predictive (goal-directed) data mining – management applications

We are seeking an experienced professional to drive the design, development, and deployment of advanced analytical solutions and machine learning models. This role will collaborate with stakeholders to extract insights from large datasets and translate them into actionable outcomes.

• Analytical Model Development: Design, develop, and deploy machine learning models and analytical solutions for business-critical problems.
• Collaboration and Communication: Collaborate with data engineers to ensure data quality, integrity, and accessibility for modeling and analysis. Analyze complex datasets using statistical and predictive modeling techniques to uncover trends and patterns.
• Solutions Development: Translate business problems into analytical solutions, defining success metrics and model evaluation criteria.
• Mentorship and Training: Mentor junior analysts and guide best practices in feature engineering, model tuning, and validation.
• Stakeholder Management: Present findings and model results to stakeholders through clear, data-driven storytelling and visualization.

• Educational Background: Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field.
• Professional Experience: 5+ years of experience in data science or applied machine learning roles.
• Technical Skills: Proficiency in Python or R, with strong experience in libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost.

This is an exciting opportunity to work on high-impact projects and contribute to driving business outcomes. As a key member of the team, you will have the chance to collaborate with talented professionals and advance your skills in data analysis and machine learning.

The successful candidate will be part of a dynamic environment that values innovation, teamwork, and continuous learning. If you are passionate about data science and eager to take on new challenges, we encourage you to apply for this opportunity.

About the opportunity

The Growth Data Science Director will lead and accelerate growth strategies across marketing optimization, product initiatives (e.g., churn reduction), ecosystem plays, and ads revenue for talabat and Quick commerce. This role requires collaboration with product teams, senior marketing, and partner leadership to drive data-driven decisions and business growth.

What’s On Your Plate?

• Data Science: Define and execute data strategies aligned with company goals, leading cross-functional teams to develop innovative data-driven products and insights that impact business outcomes.
• Strategic Leadership and Business Acumen: Demonstrate strategic leadership, articulate vision, and incorporate emerging trends and technologies to add value.
• Collaboration and Influence: Work with stakeholders including executives, product managers, engineers, and external partners; represent the organization at industry events.
• Resource Management: Manage teams, budgets, and resources; prioritize projects; coach and mentor managers.
• Strategic Hiring and Talent Development: Recruit, develop career paths, and provide feedback to team members.
• Organizational Change Management: Lead change initiatives, communicate effectively, and manage resistance.

What you need to be successful

• 8-10+ years in data science, with leadership experience in managing teams or consulting.
• Ph.D. or Master’s in relevant fields such as computer science, statistics, or data science.
• Proven leadership in fostering high-performance teams and applying data science skills to create impactful products and insights.
• Deep knowledge of statistics, causality, experimentation, and modeling.
• Business acumen with experience in quantifying impact through data initiatives.
• Strategic thinking and ability to develop data-driven roadmaps aligned with organizational goals.

Who we are

Since 2004, talabat has been Kuwait’s leading on-demand food and Q-commerce app, serving eight countries. We leverage technology to simplify life, optimize operations, and provide earning opportunities. We foster a high-performance culture, value authenticity, and are proud of our awards and diverse team of over 6,000 Talabaty committed to making a difference.

About the opportunity

The Growth Data Science Director will lead and accelerate growth strategies across marketing optimization, product initiatives (e.g., churn reduction), ecosystem plays, and ads revenue for talabat and Quick commerce. This role requires collaboration with product teams, senior marketing, and partner leadership to drive data-driven decisions and business growth.

What’s On Your Plate?

• Data Science: Define and execute data strategies aligned with company goals, leading cross-functional teams to develop innovative data-driven products and insights that impact business outcomes.
• Strategic Leadership and Business Acumen: Demonstrate strategic leadership, articulate vision, and incorporate emerging trends and technologies to add value.
• Collaboration and Influence: Work with stakeholders including executives, product managers, engineers, and external partners; represent the organization at industry events.
• Resource Management: Manage teams, budgets, and resources; prioritize projects; coach and mentor managers.
• Strategic Hiring and Talent Development: Recruit, develop career paths, and provide feedback to team members.
• Organizational Change Management: Lead change initiatives, communicate effectively, and manage resistance.

What you need to be successful

• 8-10+ years in data science, with leadership experience in managing teams or consulting.
• Ph.D. or Master’s in relevant fields such as computer science, statistics, or data science.
• Proven leadership in fostering high-performance teams and applying data science skills to create impactful products and insights.
• Deep knowledge of statistics, causality, experimentation, and modeling.
• Business acumen with experience in quantifying impact through data initiatives.
• Strategic thinking and ability to develop data-driven roadmaps aligned with organizational goals.

Who we are

Since 2004, talabat has been Kuwait’s leading on-demand food and Q-commerce app, serving eight countries. We leverage technology to simplify life, optimize operations, and provide earning opportunities. We foster a high-performance culture, value authenticity, and are proud of our awards and diverse team of over 6,000 Talabaty committed to making a difference.

Job Description
The Emirates Center for Mobility Research (ECMR) at UAE University is at the forefront of innovation in transportation and mobility solutions. Our research focuses on sustainable, smart, safe, and autonomous mobility systems, with a vision to contribute to the UAE's future as a global hub for cutting-edge transportation solutions. ECMR works on various interdisciplinary projects, from urban mobility and traffic safety to intelligent transport systems, and collaborates with industry partners, governmental bodies, and academic institutions both locally and globally.

Position: Post-Doctoral Researcher
The successful candidate will work on advanced research projects in mobility systems, smart transportation technologies, and related fields. You will collaborate closely with a multidisciplinary team of researchers, engineers, and policymakers to develop solutions that address the challenges of modern transportation and contribute to the UAE's strategic goals in sustainable mobility.

Minimum Qualification
PhD degree in Transportation Engineering or any related field.

Preferred Qualification
PhD degree in Transportation Engineering or any related field.

Expected Skills
The Research Associate is expected to:

• Conduct advanced research in one or more of the following areas: autonomous vehicles, smart cities, sustainable transportation, traffic systems, electric vehicles, and connected transport networks.
• Develop models, algorithms, and simulations for real-world transportation problems.
• Collaborate on interdisciplinary projects with team members, including faculty, industry experts, and government stakeholders.
• Assist and co-supervise PhD and Masters students.
• Prepare and publish research findings in peer-reviewed journals and present at international conferences.
• Contribute to grant proposals and engage with funding agencies.
• Mentor graduate and undergraduate students involved in mobility research projects.
• Support the Center's outreach and knowledge-sharing initiatives.
• Aid in the research center's administrative duties including development of marketing material, conducting follow-up meetings with potential clients and leads, writing formal letters, and obtaining necessary approvals.
• Maintain and monitor project plans, project schedules, work hours, budgets, and expenditures.