21 Data Interpretation jobs in the United Arab Emirates

The successful candidate will develop new features and extend existing functionalities across the full stack (frontend and backend) of a data visualization platform using ReactJS, TypeScript, Python, and Flask.

They will also customize and build advanced interactive dashboards and data visualizations tailored to business analytics requirements.

Additionally, they will integrate and enhance custom chart capabilities leveraging the native charting features, including developing dropdown-style slicer charts similar to those found in Power BI.

The ideal candidate will have experience with Docker containerization and proficiency in backend development with Python and Flask.

They should also be familiar with the infrastructure, deployment, and administration best practices, as well as data visualization, data exploration, and business intelligence solutions.

A strong understanding of data science and analytics workflows is also essential.

Key Responsibilities:

• Develop new features and extend existing functionalities across the full stack (frontend and backend)
• Customize and build advanced interactive dashboards and data visualizations
• Integrate and enhance custom chart capabilities
• Troubleshoot and resolve errors related to numeric-type charts handling small datasets
• Enable advanced sorting functionalities within charts
• Ensure optimal user experience through seamless interaction with custom-developed charts and UI components

Requirements:

• Strong frontend development experience with ReactJS and TypeScript
• Proficient in backend development with Python and Flask
• Extensive experience with Docker containerization
• Solid expertise using UI libraries and custom plugin development
• Familiarity with the infrastructure, deployment, and administration best practices
• Data visualization, data exploration, and business intelligence solutions
• Experience handling business analytics use-cases and SQL editor integrations
• Understanding of data science and analytics workflows

Bonus Points:

• Infrastructure, administration, and deployment
• Dashboard development and best practices
• Customized features and integrations
• Strategic BI roadmaps and business analytics expansion

This description does not constitute an offer or commitment. Applicants are advised to research the bonafides of the prospective employer independently. We do NOT endorse any requests for money payments and strictly advice against sharing personal information.

We are seeking a skilled developer to join our team in developing new features and extending existing functionalities across the full stack (frontend and backend) of Apache Superset.

The successful candidate will work with ReactJS, TypeScript, Python, and Flask to create advanced interactive dashboards and data visualizations tailored to business analytics requirements.

• About this role:
• This is a unique opportunity for an experienced Full Stack Developer to contribute to the growth and success of our company by building innovative solutions using cutting-edge technologies.
• You will be responsible for designing, implementing, and maintaining high-quality software applications that meet the needs of our customers.
• Additionally, you will collaborate with other teams to integrate and enhance custom chart capabilities leveraging Apache Superset's native charting features.
• The ideal candidate will have strong problem-solving skills and be able to troubleshoot and resolve errors efficiently.
• Apart from development tasks, you will also ensure optimal user experience through seamless interaction with custom-developed charts and UI components.

Main Responsibilities:

We are seeking a highly motivated and detail-oriented Pharmaceutical Data Analyst to join our dynamic team. As a key member of the Commercial Operations department, you will have the opportunity to contribute to the transformation, harmonization, and continuous improvement of analysis and insights creation by leveraging innovative data platforms to deliver actionable insights to the business.

• Develop and implement data analytics solutions to drive business decisions
• Analyze complex data sets to identify trends and opportunities for growth
• Collaborate with cross-functional teams to integrate data insights into business strategies

• Bachelor's degree in Data Science, Statistics, or related field
• Proficiency in data analysis tools and technologies such as Excel, SQL, and Tableau
• Strong analytical and problem-solving skills

• A competitive salary and benefits package
• Ongoing training and development opportunities
• A collaborative and dynamic work environment

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

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JOB PURPOSE
Support the Enterprise Command and Control Departments’ roles pertaining to transportation modelling, through

Job Description
JOB PURPOSE
Support the Enterprise Command and Control Departments’ roles pertaining to transportation modelling, through
the application of transportation planning and engineering logic to leverage data analytics and transportation
modeling, aiming to optimize transportation systems and enhance the overall efficiency of Dubai's transportation
network.
Key Results Accountabilities
# Analyze the relevant data to support decisions related to transportation network planning and ensure
updating of the model and its databases based on modifications and additions made on the roads and public
transportation networks and related urban and population plans
# Utilize transportation models and simulation software to assess the impact of proposed infrastructure
changes, policy and strategies, planned and unplanned mega events, to conduct scenario analysis and evaluate
the effectiveness of different solutions
# Develop, review, and update policies, procedures, and other technically specialized documents concerning the
areas of expertise and in coordination with the stakeholders and alignment with RTA’s document management
systems, in addition to contributing to the formulation and implementation of other transportation-related
policies, guidelines, and standards
# Support the development of accurate demand forecasts for various transportation modes and evaluate the
capacity requirements of the transportation network. Provide inputs for infrastructure planning, service
optimization, and the development of transportation policies
# Establish performance metrics and KPIs to monitor the effectiveness of transportation initiatives. Develop
monitoring systems and prepare regular reports to evaluate the impact of implemented measures and identify
areas for improvement
# Prepare detailed engineering reports by analyzing data related to Population Density, Pedestrians, Congestion
Information, Historical Traffic, Origin Destination, Metro, Tram, Transit and taxi information, in addition to
contributing to studies pertaining to adding new modes in near future, e.g., electrical scooter, aerial taxi, etc
# Contribute to the organizational knowledge sharing and specialized training plans, through conducting
specialized workshops in a formal and educational context, and induction programs for new employees, within
the area of expertise
# Conduct specialized benchmarking studies in the field of work and tasks assigned to ensure the distinguished
and pioneering position of the organization in accordance with the strategic directions of RTA. This includes,
but is not limited to conducting research, pilot studies, and experimental projects to explore innovative
solutions and contribute to the advancement of the field
# Perform other related duties and responsibilities associated with the position, or any additional responsibilities
as advised by the direct Line Manager or Department Director
# Manage ECCD projects, including planning, budgeting, and resource allocation. Ensure projects are delivered
within scope, on time, and within budget, while maintaining high quality standards
# Supervise the operation and maintenance of the real-time transportation model, ensuring its reliability and
responsiveness. Monitor and analyze model outputs to identify deviations, anomalies, and opportunities for
immediate interventions to improve the efficiency and performance of the transportation network
# Work on the real-time transportation model development, through incorporating different modes of
transportation into the model to analyze intermodal connectivity and develop integrated transportation
solutions, and accurate, up-to-date insights.
Qualifications
Technical Competencies
# Stakeholder Management
# Administrative Support
# Transportation Planning
# Traffic Engineering
Education
# Master’s degree in Transportation Planning and / or Traffic Engineering from a recognized university with
Minimum of 9 years of transportation planning & traffic engineering experience
Skills
# Full knowledge of principles and practices related to traffic operations and planning.
# Results-driven achiever with exemplary planning and organizational skills, along with a high degree of detail
orientation
# Statistical methods and research techniques applicable to the preparation of transportation planning
documents
# Knowledge of methods & techniques of effective technical report preparation, presentation, and policy
development
# Experience in software related to transportation planning and forecasting, travel demand modelling and data
analysis such as VISUM, VISSIM, EMME/2, Synchro, Sidra, MS Access & Excel
# Full knowledge about Four Steps Transportation Modelling and principles and practices of traffic and
transportation planning and travel demand modelling
Job Category
Statistical
Advertiser
Roads and Transport Authority
Department
Enterprise Command & Control
Educational-level
Master
Required Nationality
All Nationalities (Priority for UAE National)
Monthly Salary
Unspecified
Schedule-Time
Full time
Job Posting
01/05/2025
Unposting Date
02/06/2025

• Seniority levelMid-Senior level

• Employment typeFull-time

• Job functionProject Management and Information Technology
• IndustriesGovernment Administration

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JOB PURPOSE
Support the Enterprise Command and Control Departments’ roles pertaining to transportation modelling, through

Job Description
JOB PURPOSE
Support the Enterprise Command and Control Departments’ roles pertaining to transportation modelling, through
the application of transportation planning and engineering logic to leverage data analytics and transportation
modeling, aiming to optimize transportation systems and enhance the overall efficiency of Dubai's transportation
network.
Key Results Accountabilities
# Analyze the relevant data to support decisions related to transportation network planning and ensure
updating of the model and its databases based on modifications and additions made on the roads and public
transportation networks and related urban and population plans
# Utilize transportation models and simulation software to assess the impact of proposed infrastructure
changes, policy and strategies, planned and unplanned mega events, to conduct scenario analysis and evaluate
the effectiveness of different solutions
# Develop, review, and update policies, procedures, and other technically specialized documents concerning the
areas of expertise and in coordination with the stakeholders and alignment with RTA’s document management
systems, in addition to contributing to the formulation and implementation of other transportation-related
policies, guidelines, and standards
# Support the development of accurate demand forecasts for various transportation modes and evaluate the
capacity requirements of the transportation network. Provide inputs for infrastructure planning, service
optimization, and the development of transportation policies
# Establish performance metrics and KPIs to monitor the effectiveness of transportation initiatives. Develop
monitoring systems and prepare regular reports to evaluate the impact of implemented measures and identify
areas for improvement
# Prepare detailed engineering reports by analyzing data related to Population Density, Pedestrians, Congestion
Information, Historical Traffic, Origin Destination, Metro, Tram, Transit and taxi information, in addition to
contributing to studies pertaining to adding new modes in near future, e.g., electrical scooter, aerial taxi, etc
# Contribute to the organizational knowledge sharing and specialized training plans, through conducting
specialized workshops in a formal and educational context, and induction programs for new employees, within
the area of expertise
# Conduct specialized benchmarking studies in the field of work and tasks assigned to ensure the distinguished
and pioneering position of the organization in accordance with the strategic directions of RTA. This includes,
but is not limited to conducting research, pilot studies, and experimental projects to explore innovative
solutions and contribute to the advancement of the field
# Perform other related duties and responsibilities associated with the position, or any additional responsibilities
as advised by the direct Line Manager or Department Director
# Manage ECCD projects, including planning, budgeting, and resource allocation. Ensure projects are delivered
within scope, on time, and within budget, while maintaining high quality standards
# Supervise the operation and maintenance of the real-time transportation model, ensuring its reliability and
responsiveness. Monitor and analyze model outputs to identify deviations, anomalies, and opportunities for
immediate interventions to improve the efficiency and performance of the transportation network
# Work on the real-time transportation model development, through incorporating different modes of
transportation into the model to analyze intermodal connectivity and develop integrated transportation
solutions, and accurate, up-to-date insights.
Qualifications
Technical Competencies
# Stakeholder Management
# Administrative Support
# Transportation Planning
# Traffic Engineering
Education
# Master’s degree in Transportation Planning and / or Traffic Engineering from a recognized university with
Minimum of 9 years of transportation planning & traffic engineering experience
Skills
# Full knowledge of principles and practices related to traffic operations and planning.
# Results-driven achiever with exemplary planning and organizational skills, along with a high degree of detail
orientation
# Statistical methods and research techniques applicable to the preparation of transportation planning
documents
# Knowledge of methods & techniques of effective technical report preparation, presentation, and policy
development
# Experience in software related to transportation planning and forecasting, travel demand modelling and data
analysis such as VISUM, VISSIM, EMME/2, Synchro, Sidra, MS Access & Excel
# Full knowledge about Four Steps Transportation Modelling and principles and practices of traffic and
transportation planning and travel demand modelling
Job Category
Statistical
Advertiser
Roads and Transport Authority
Department
Enterprise Command & Control
Educational-level
Master
Required Nationality
All Nationalities (Priority for UAE National)
Monthly Salary
Unspecified
Schedule-Time
Full time
Job Posting
01/05/2025
Unposting Date
01/06/2025

• Seniority levelMid-Senior level

• Employment typeFull-time

• Job functionProject Management and Information Technology
• IndustriesGovernment Administration

Referrals increase your chances of interviewing at Dubai Careers - A Smart Dubai Initiative by 2x

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

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