29 Feature Engineering jobs in Dubai

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.

We are seeking a skilled professional to lead our data analysis team. As a Lead Data Analyst, you will be responsible for overseeing a team of analysts and collaborating with developers and stakeholders to ensure software meets business needs.

• Manage a team of data analysts
• Create data marts and data lakes using mappings
• Design user interfaces and dashboards for data visualization and interaction
• Test and validate software and data products for accuracy and reliability

• Bachelor's or master's degree in Computer Science, IT, or related field
• Experience with data processing and analysis using Data Bricks
• Expert-level proficiency in SQL, Python, SAS/R, Spark
• Deployment experience in databases, server/cloud environments (AWS, Azure), APIs, ODBCs, web apps

• Career Growth: Opportunities for professional development and advancement
• Performance-Based Compensation: Competitive pay linked to performance
• Inclusive Culture: Join a collaborative team that values innovation and every voice

This is an exciting opportunity to work with a talented team and contribute to our success.

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.

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Bayut & dubizzle - The Arab World's only Homegrown Unicorn Business is now inviting applications for internships of 6 months duration in our Business Intelligence department.

World-class mentors, fast paced & high performing work environment, our open culture and the opportunity to make an impact are just a few of the reasons why our internship program is highly sought after.

As a Machine Learning Intern, you will be participating in exciting projects covering the end-to-end Data Science lifecycle – from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.

You will work in a modern cloud-based data warehousing environment hosting Machine Learning models alongside alongside a team of diverse, intense and interesting co-workers. You will liaise with other departments – such as product & tech, the core business verticals, trust & safety, finance and others – to enable them to be successful.

In this role, you will:

• Query large datasets with SQL and feed ML models.
• Perform data exploration to find patterns in the data and understand the state and quality of the data available.
• Utilize Python code for analyzing data and building statistical models to solve specific business problems.
• Evaluate ML models and fine tune model parameters considering the business problem behind.
• Collaborate with senior peers to Deploy ML models in production.
• Build customer-facing reporting tools to provide insights and metrics which track system performance.
• Being part and contributing towards a strong team culture and ambition to be on the cutting edge of big data
• Participate in the off-hours on call stability rotation to support live ML models

• Bachelor’s degree in AI, Statistics, Math, Operations Research, Engineering, Computer Science, or a related quantitative field.
• Statistical modelling and math
• Basic knowledge of Machine learning algorithms.
• Basic knowledge of SQL.
• Basic knowledge of visualization tools such as Periscope
• Excellent verbal and written communication.
• Strong problem solving skills.

• Ability to contribute to a platform used by more than 5M users in UAE and other platforms in the region.
• Strengthen your resume and build your network.
• Opportunity to find a full time career with the region's leading organization.
• Working in a multicultural environment with over 50 different nationalities
• Access to the Learning & Development tools and courses provided by the company.

Bayut & dubizzle is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

#dubizzle

Messilat is seeking a talented MLOps Engineer for our client's team. The perfect candidate will excel in deploying models, managing microservices, utilizing Docker, and maintaining Kubernetes. Our client is also exploring AI applications in customer service, cybersecurity, and compliance.

Key Responsibilities

• Transition models from development to production, ensuring scalability and high performance. Collaborate with development teams for seamless model deployment.
• Implement monitoring and maintenance strategies for deployed models to ensure ongoing accuracy and reliability.
• Maintain Kubernetes clusters to ensure high availability and performance.
• Work with cross-functional teams to understand business requirements and deliver effective machine learning solutions.
• Develop and implement strategies that optimize efficiency and data quality.

Qualifications

• Minimum of 3 years of experience in MLOps or a related field.
• Expertise in model deployment, containerization, and orchestration (e.g., Docker, Kubernetes).
• Familiarity with cloud platforms (e.g., AWS, or on-premises) for model deployment and management.
• Experience in deploying AI models and managing their lifecycle.
• Proficiency in Python for scripting and automation.
• Prior experience in addressing scalability and pricing concerns in ML operations.

Skills

• Model deployment, monitoring, Docker, Kubernetes, AWS Cloud services, on-premises deployment, collaboration.

If you are passionate about MLOps and looking for a challenging role where you can make a significant impact, we would love to hear from you. Apply today!

We are seeking a talented Machine Learning Engineer to join our data science team. The ideal candidate will be responsible for developing and implementing machine learning models and algorithms that solve complex business problems. You will work closely with data scientists, software engineers, and stakeholders to deliver scalable solutions.

Responsibilities:

• Design, build, and deploy machine learning models and algorithms
• Collaborate with data scientists to refine data features and enhance model performance
• Optimize and improve existing machine learning models for efficiency and accuracy
• Conduct data preprocessing, feature engineering, and data analysis
• Monitor and maintain models in production to ensure they operate effectively
• Document and communicate model designs and performance metrics to stakeholders
• Stay updated on the latest industry trends and advancements in machine learning and AI
• Participate in code reviews and contribute to a culture of continuous improvement

Profile requirements:

• Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field
• Proven experience as a Machine Learning Engineer or in a similar role
• Proficiency in programming languages such as Python, Java, or R
• Experience with machine learning frameworks and libraries (e.g.,AWS BedRock, Amazon SageMaker, TensorFlow, PyTorch, Scikit-learn)
• Strong understanding of algorithms, data structures, and software engineering principles
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and tools for deploying machine learning models
• Knowledge of data manipulation and analysis tools (e.g., SQL, Pandas, NumPy)
• Excellent problem-solving skills and ability to work collaboratively in a team environment
• Experience with deep learning and natural language processing (NLP) techniques
• Understanding of model interpretability and explainability
• Perform statistical analysis, and train and retrain systems to optimize performance

Preferred Skills:

• Familiarity with version control systems (e.g., Git) and CI/CD practices
• Experience with AI/GenAI
• Experience with AWS data services (e.g., AWS EMR, AWS Glue, AWS Athena)

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