29 Market Research Analyst jobs in Dubai

Consumer Insights Graduate Trainee - Jan 2026 at L'Oréal

A Graduate Program at L'Oréal Middle East will allow you to gain strong professional experience, learn and connect with the best in industry. Come and join our Consumer and Market Insights team for a 9–12 month assignment.

• Drive, collect and analyze data (brand, product experiences, market & shopper, social insights). Drive insights on consumer & shopper journey for Activation/Go to Market.
• Integrate market data and insights into the consumer studies and analysis
• Propose and formalize the framework of projects (objectives, timing, resources) and participate in the brief
• Use and develop methods to answer hypotheses in the brief
• Plan and carry out consumer and market studies (market data consolidation, panels follow-up, brand and category evolution, growth opportunities)
• Analyze results and translate data into meaningful consumer and market insights (including new trends, prospective/innovation and socio-economical data)
• Participate in building and transmitting a consumer-centric culture
• Contribute to data intelligence and develop data and tools software expertise
• Cooperate with internal and external cross-functional stakeholders using collaborative and agile group tools and project methods
• Present and communicate sharp, clear messages actionable for management and internal stakeholders

• Confident in using Microsoft Office: Excel, Word, Outlook, PowerPoint
• Analytical mindset, statistics-savvy and able to summarize 360 data
• Communicates with impact, clarity and conviction
• Future-oriented and able to detect new trends
• Ability to work in a multi-functional environment and interact effectively with business partners outside CMI
• Able to operate in a fast-moving environment and manage time efficiently
• FMCG/Beauty, Market research, Marketing, Digital experience is a plus
• Fluent in Arabic (Written and Spoken)

• Final year student or recent graduate (less than 2 years)
• Available for at least 6–12 months

Ready to start your L'Oréal adventure? Let us know more about you by applying now to this program

• Entry level

• Full-time

• Marketing, Other, and Consulting

• Manufacturing and Personal Care Product Manufacturing

Job Title: Data Expert

At our organization, we are seeking a talented Data Expert to join our team. As a key member of our data science team, you will play a vital role in helping us make informed decisions by leveraging data insights and analysis.

Key Responsibilities:

• Design and implement advanced statistical models to analyze complex data sets.
• Develop and maintain databases to store and manage large datasets.
• Collaborate with cross-functional teams to identify business needs and develop solutions.
• Communicate findings and insights effectively to both technical and non-technical stakeholders through reports, presentations, and visualizations.
• Stay up-to-date with the latest advancements in data science, machine learning, and AI technologies.

Required Skills and Qualifications:

• Bachelor's degree in statistics, applied mathematics, or related discipline.
• Minimum of 4-6 years of experience in a similar role.
• Proficiency with data mining, mathematics, and statistical analysis.
• Advanced pattern recognition and predictive modeling experience.
• Experience with Excel, Tableau/Looker Studio, SQL, and programming languages such as Python and R.
• Storytelling and data visualization skills.
• Comfort working in a dynamic, data-oriented team with several ongoing concurrent projects.

Preferred Qualifications:

• Master's degree in stats, applied math, or related discipline.
• Experience with NoSQL, Pig, Hive, and PySpark/Big Query.

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

• Bachelors 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 highly skilled Data Analyst to join our team in Dubai. As a key member of our organization, you will be responsible for collecting, organizing, and analyzing data that informs business decisions.

- Collect and analyze large datasets to identify trends and patterns
- Develop and maintain databases to ensure accurate data storage and retrieval
- Create data visualizations to effectively communicate insights to stakeholders
- Collaborate with cross-functional teams to drive business growth through data-driven decision making

- Bachelor's degree in Statistics, Mathematics, Computer Science, or related field
- Proficient in database management systems such as SQL and programming languages like Python
- Excellent problem-solving skills and ability to interpret complex data quickly and accurately
- Strong communication and presentation skills, with ability to clearly convey findings to colleagues and stakeholders
- Ability to work independently and collaboratively as part of a team

- Salary of 1300 AED per month
- Opportunity to work in a dynamic and growing industry
- Chance to develop your skills and expertise in data analysis

This is an excellent opportunity for individuals who are passionate about data and its applications. If you are motivated, detail-oriented, and able to work well under pressure, we encourage you to apply.

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

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

This 5-day course focuses on leveraging data analytics as a decision support tool in management. Data analytics is increasingly being used by professionals to make informed business decisions.

• Explore the applications of data analytics in management practice
• Leverage statistical evidence and integrate quantitative reasoning into decision making
• Promote confidence in using evidence-based information

• Explain the scope and structure of data analytics
• Apply cross-sectional data analytics techniques
• Interpret and critically assess statistical evidence
• Identify relevant applications of data analytics in practice

• Management support professionals
• Data analysts regularly encountering data/analytical information
• Professionals seeking to derive greater decision-making value from data analytics

Key Skills:

• Ability to interpret statistical evidence
• Integration of quantitative reasoning into decision making
• Appreciation of data analytics applications in management

Benefits:

• Improved decision-making skills through data-driven insights
• Enhanced understanding of data analytics in management
• Increased confidence in using evidence-based information

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.

Policy Researcher

We are seeking a highly motivated and skilled Policy Researcher to join our team. As a Policy Researcher, you will play a crucial role in shaping the future of policy research and human rights.

In this role, you will be responsible for conducting in-depth research on various policy issues, analyzing data, and developing strategic recommendations to inform policy decisions.