12 Data Analysis jobs in the United Arab Emirates

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

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.

Role Summary

As the leading delivery company in the region we have a great responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential we need to advance our platform to become much more intelligent in how it understands and serves our users.
As a data scientist on the analysis track your mission will be to improve the quality of the decisions made across product and business via relevant, reliable, and actionable data. You will own a particular domain across product and business and will work closely with the corresponding product and business managers as part of a talented team of data scientists and data engineers. You will own the entire data value chain including logging, data modeling, analysis, reporting, and experimentation.

Whats On Your Plate

• Leveraging ambiguous business problems as opportunities to drive objective criteria using data.
• Developing a deep understanding of the product experiences and business processes that make up your area of focus.
• Developing a deep familiarity with the source data and its generating systems through documentation, interacting with the engineering teams, and systematic data profiling.
• Contributing heavily to the design and maintenance of the data models that allow us to measure performance and comprehend performance drivers for your area of focus.
• Working closely with product and business teams to identify important questions that can be answered effectively with data.
• Delivering well-formed, relevant, reliable, and actionable insights and recommendations to support data-driven decision making through deep analysis and automated reports.
• Designing, planning, and analyzing experiments (A/B and multivariate tests).
• Supporting product and business managers with KPI design and goal setting.
• Mentoring other data scientists in their growth journeys.
• Contributing to improving our ways of work, our tooling, and our internal training programs.

What Did We Order
Technical Experience

• Excellent SQL.
• Competence with reproducible data analysis using Python or R.
• Familiarity with data modeling and dimensional design.
• Strong command over the entire data analysis lifecycle including problem formulation, data auditing, rigorous analysis, interpretation, recommendations, and presentation.
• Familiarity with different types of analysis including descriptive, exploratory, inferential, causal, and predictive analysis.
• Deep understanding of the various experiment design and analysis workflows and the corresponding statistical techniques.
• Familiarity with product data (impressions, events) and product health measurement (conversion, engagement, retention).
• Familiarity with BigQuery and the Google Cloud Platform is a plus.
• Data engineering and data pipeline development experience (e.g. via Airflow) is a plus.
• Experience with classical ML frameworks (e.g. Scikit-learn, XGBoost, LightGBM) is a plus.

Qualifications:

• Bachelor's degree in engineering, computer science, technology, or similar fields. A postgraduate degree is a plus but not required.
• 3 years of overall experience working in data science and machine learning.
• Experience doing data science in an online consumer product setting is a plus.
• A good problem solver with a figure-it-out growth mindset.
• An excellent collaborator.
• An excellent communicator.
• A strong sense of ownership and accountability.
• A keep-it-simple approach to #makeithappen.

Remote Work:

No

Employment Type:

Full-time

At General Motors we pride ourselves on designing, building and selling the world's best vehicles. We are seeking a new generation of visionaries to help launch bold engineering and business initiatives, and shape new directions for General Motors. As an intern you will gain hands-on career specific experiences to maximize your real-world potential.

Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to the office at minimum three times per week or other frequency dictated by the business and two times per week remote.

Your Role:

As a Data Engineering and Analysis Intern, you’ll have the opportunity to gain hands-on experience in data-driven decision-making and contribute to our global sales operations. You will collaborate with senior team members, work on data collection, analysis, and reporting, and help optimize business processes using data science techniques.

What You'll Do:

• Assist in gathering and preparing data from various sources
• Clean, transform, and analyze data to ensure quality and accuracy
• Support data analysis, hypothesis testing, and exploratory data analysis (EDA)
• Help build and validate predictive models using basic machine learning techniques
• Generate reports and create data visualizations to highlight business insights
• Collaborate with cross-functional teams (Sales, Finance, CRM, Omnichannel) to support data-driven solutions
• Contribute to business performance tracking, including dashboards and KPIs
• Participate in training and mentorship opportunities to enhance your technical skills

Your Skills & Abilities:

• Currently undergoing bachelor's or master's degree in data science, Data Engineering, Business Analytics, or a related field
• Basic knowledge of programming languages (Python preferred) and data analysis tools (e.g., SQL, Excel)
• Basic knowledge of data visualization tools (Power BI, Tableau) is a plus
• Completed coursework in AI, machine learning, deep learning, and natural language processing (NLP)
• Worked on academic projects involving generative models (like GPT-3, GANs) or reinforcement learning

What We Offer:

• Mentorship from experienced professionals in business and data
• Exposure to real-world data challenges and solutions
• Opportunity to contribute to meaningful projects that impact business outcomes