284 Key Performance Indicators 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

• 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

Business Analyst – Riyadh Based

We are seeking a highly skilled Business Analyst to join our team in Riyadh, Saudi Arabia.

• A strong understanding of market risk measurement and management is essential for this role.
• The ideal candidate will have a thorough knowledge of quantitative skills and the ability to support clients across the region. They will be responsible for managing client relationships and developing expertise in data analysis.
• Key responsibilities include:
1. Develop strategic plans to ensure client retention and satisfaction
2. Stay up-to-date with the latest market trends and regulatory landscape
3. Identify opportunities to increase client usage of data analysis tools
4. Work closely with the sales team on cross-product selling opportunities
5. Engage with clients to inform them of product roadmaps and solicit feedback regarding future development
6. Collaborate with internal teams to ensure client requests are managed appropriately
7. Respond to detailed client enquiries and hold advanced training workshops

This is an exciting opportunity to work with a leading provider of critical decision support tools and services for the global investment community. We offer a range of benefits, including flexible working arrangements, advanced technology, and collaborative workspaces.

As a Business Analyst at MSCI, you'll be part of an industry-leading network of creative, curious, and entrepreneurial pioneers who are passionate about making a difference through their work.

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

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.

J-18808-Ljbffr

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

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

Our client is a dynamic and progressive energy business with a strong focus on energy transition and decarbonisation. With operations across multiple jurisdictions, the organisation is known for maximising value from mature assets while embracing innovative, sustainable energy solutions

• Work closely with the Decommissioning Directorate to support monthly performance reporting and quarterly business reviews.
• Review and validate monthly Value of Work Done (VOWD) to ensure accurate financial reporting.
• Maintain accounting records for Joint Venture (JV) assets and ensure compliance with Joint Operating Agreements (JOA) and accounting standards.
• Support the preparation of budget and forecast submissions, including annual business planning activities.
• Assist with the month-end close process, ensuring accurate journal entries, reconciliations, and reporting.
• Monitor and review gross transactions, ensuring correctness before running monthly JV cutback processes.
• Prepare and issue monthly JV billings, cash calls, cost carry statements, and bank reconciliations.
• Ensure timely and accurate reporting of Authority for Expenditure (AFE) to both internal stakeholders and JV partners.
• Manage partner queries related to billings, cash calls, and cost allocations.
• Coordinate and support partner Joint Venture audits, including preparation, documentation, and query resolution.
• Complete monthly balance sheet reconciliations and take corrective actions where needed.
• Provide accurate and timely information for internal and external financial reporting teams.
• Support JV finance and operating committee meetings as needed.
• Collaborate with cross-functional teams including accounts payable and operations to resolve discrepancies and support business objectives.
• Ensure adherence to internal controls, accounting policies, and financial governance standards

• Professionally qualified accountant (CA, CIMA, ACCA, or equivalent).
• 5+ years of post-qualification experience, ideally with prior exposure to JV or project-based accounting.
• Proficient in SAP, Oracle, SUN, or other financial ERP systems.
• Strong Excel and analytical skills.
• Previous experience working with Joint Ventures or decommissioning projects is an advantage.

The Business Analyst II plays a key role in analyzing business needs and supporting product development through comprehensive documentation. The role involves gathering requirements, conducting gap analyses, and preparing clear, actionable documentation to support solution delivery.

Key Responsibilities

• Conduct requirement-gathering sessions, interviews, and workshops.
• Analyze and document current and future business processes using BPMN.
• Create BRDs, FRDs, use cases, user stories, and acceptance criteria.
• Design wireframes, mockups, and user flows to visualize features.
• Define MVP scopes and break down epics into backlog items.
• Collaborate with developers to clarify business logic and constraints.
• Review test cases and support UAT, defect tracking, and validation.
• Manage requirement changes and maintain version control.
• Lead stakeholder walkthroughs and demos to confirm requirement fulfillment.
• Prepare SOPs, user manuals, and onboarding materials.
• Contribute to RFPs, RFQs, and bid evaluations.
• Ensure consistent communication with stakeholders and project teams.
• Participate in Agile ceremonies and support cross-functional alignment.
• May mentor junior analysts.

• Bachelor’s degree in a relevant field.
• Business Analysis certification (e.g., CCBA, BPMN); Scrum certification is a plus.

• 2–5 years in business analysis with exposure to Agile practices.

• Strong analytical, communication, and documentation skills.
• Proficiency in Jira, MS Office, Visio, and understanding of SDLC.
• Detail-oriented, adaptable, and team-focused.
• Fluent in English (written and spoken).