21 Data Science Manager jobs in Dubai

Job Description:

Job Title: Data Analytics and Strategy Manager Carat

Work Location: Dubai, UAE

Job Level: Manager

Job Type: Full-time (Hybrid)

About Dentsu International:

Dentsu is one of the largest marketing and advertising groups, providing a full suite of creative, data, technology, and media services to clients across 145 countries.

We empower leading brands to create better customer experiences through digital and creative transformation. Our expertise spans creative excellence, customer engagement, media, enterprise marketing technology, and more, serving a diverse portfolio of Fortune 100 companies and iconic brands worldwide.

Learn more about us here: (Insert link if available)

Role:

The Data and Analytics Strategy Manager leads the agency's data strategy and analytics initiatives. The core responsibility is to develop and implement data-driven strategies to foster business growth and enhance decision-making processes across the organization.

Key Responsibilities:

• Build strong relationships and collaborate with operational, product, business performance, data science, and data visualization leads.
• Analyze and correlate data from various sources (research, sales, media metrics, etc.).
• Produce insights and develop viewpoints based on data outputs.
• Work with business leads to create data and analytics solutions (e.g., Google Analytics, Data Visualization).
• Report to the Performance Director to drive performance and business intelligence for clients.
• Develop and execute the overall data and analytics strategy aligned with company goals.
• Establish and enforce data governance policies ensuring data quality, consistency, and security.
• Lead a team of data analysts and data scientists to deliver actionable insights.
• Collaborate with stakeholders to understand data needs and deliver appropriate solutions.
• Design measurement frameworks based on goals and KPIs to evaluate data initiatives.
• Evaluate and adopt the latest data technologies and tools.
• Coordinate dashboard and report development with the data science team and other leaders.
• Stay updated on industry trends to improve data strategies and processes, collaborating with partners like Google, Meta, Tableau, Salesforce, etc.

Key Competencies:

• AI & Machine Learning: Design and deploy advanced analytics and ML models (e.g., fraud detection, recommender systems).
• Marketing & Customer Analytics: Campaign measurement, segmentation, churn prediction, customer LTV, media mix modeling, ROI optimization.
• Causal Inference & Statistical Modeling: Impact analysis and marketing event evaluation.

Leadership & Strategy:

• Team Leadership: Manage data scientists, data engineers, and BI analysts.
• Stakeholder Management: Engage with CXOs and business leaders.
• Program & Project Management: Lead end-to-end data science projects across industries and regions.

Tech Stack & Tools:

• Languages: Python, R, SQL, PySpark, Scala.
• ML Frameworks: TensorFlow, Keras, XGBoost, SVM, GBM.
• Platforms & Tools: AWS, GCP, Azure, Snowflake, Databricks, Tableau, SAS.

Industries Served:

Retail, Finance, CPG, Automotive, Technology (highly preferred).

What We Offer:

Financial Compensation:

• Competitive package, annual bonus, and return tickets to home country.

Health & Wellbeing:

• Flexible hybrid work, private healthcare, wellness days.

Company Culture & Perks:

• Diverse, collaborative environment, team socials, casual dress code.

Professional Development:

• Access to Dentsu University, internal mobility, regional exposure.

Diversity & Inclusion:

Dentsu is committed to equity and diversity, fostering an inclusive environment where everyone can bring their whole self to work.

Application Process:

Please apply online. If your profile matches, our recruiters will contact you. If not, your profile will be stored for future opportunities.

Location: Dubai

Brand: Dentsu

Time Type: Full-time

Contract Type: Permanent

Required Experience: Manager

About the opportunity

Role Summary

As a Senior Manager leading the Growth Data Science unit, you will play a pivotal role in leading and accelerating growth strategies across multiple dimensions, including marketing optimization and efficiency, growth product initiatives (e.g., churn reduction), ecosystem plays (e.g., subscription models and rewards), and ads revenue optimization. This leadership position will require close collaboration with product teams, senior marketing and partner growth leadership, ultimately driving data-driven decision-making and achieving transformative business growth.

You will collaborate closely with business leaders, and a dynamic team of data scientists and engineers. Your leadership will ensure the seamless integration of the data value chain—from data collection and modeling to analysis, reporting, and experimentation—ultimately empowering Talabat to achieve operational excellence and unparalleled customer satisfaction.

What’s On Your Plate?

Responsibilities:

• Lead the strategic vision for harnessing data to refine and enhance logistics operations. This involves identifying key opportunities for process optimization, cost reduction, and service quality improvements, ensuring that data science initiatives are perfectly aligned with Talabat’s broader business goals.

• Champion the adoption of a data-driven culture within logistics operations, emphasizing the importance of basing decisions on rigorous data analysis and actionable insights. This includes promoting the use of advanced analytics and data science methodologies across all levels of logistics operations.

• Build and maintain strong collaborative relationships with key stakeholders across product, business, and engineering teams. Ensure that data science projects are integrated with and supportive of overall business strategies, fostering a cohesive approach to achieving Talabat’s objectives.

• Guide, mentor, and develop a highly skilled team of data scientists and data analysts. Set clear performance goals, facilitate professional development opportunities, and foster a supportive and innovative work environment that attracts top talent.

• Spearhead innovative data science projects, including the application of predictive analytics, machine learning models, and optimization algorithms. Focus on projects that have the potential to significantly impact logistics efficiency and customer satisfaction.

• Ensure the development and maintenance of a robust and scalable data infrastructure that supports advanced analytics and data science activities. This includes advocating for best practices in data governance, quality control, and compliance with relevant data protection regulations.

• Oversee the generation of insightful analytical reports and dashboards that track key performance indicators (KPIs) and provide strategic insights to both the logistics team and senior management. Ensure that these insights are actionable and contribute to informed decision-making processes.

• Serve as a key point of communication between the data science unit and both internal and external stakeholders. Translate complex data-driven insights into clear, understandable, and actionable recommendations for various audiences.

• Stay abreast of the latest trends and advancements in data science, logistics, and technology. Incorporate cutting-edge practices and tools into Talabat’s data science strategy to maintain a competitive edge and foster continuous improvement.

• Effectively manage resources and priorities to strike a balance between long-term strategic initiatives and immediate operational needs. Ensure that the data science team’s efforts are focused on projects with the highest potential for positive impact on Talabat’s operations.

• Design, implement, and manage experimental frameworks, such as A/B testing, to validate new ideas and measure their impact on logistics performance. Use these insights to guide continuous improvement efforts.

• Provide expert analytical support to cross-functional teams, assisting in the development of KPIs and goal-setting processes that align with Talabat’s strategic objectives.

• Lead by example to cultivate an environment of excellence and innovation within the data science team. Encourage creative thinking, continuous learning, and the exploration of new ideas to drive forward Talabat’s logistics operations.

What you need to be successful

What Did We Order?

Technical Expertise:

• Proficient in the full data analysis lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, and presentation.

• Advanced skills in data analysis tools and programming languages such as Python, R, and SQL.

• Demonstrated expertise in data modeling, dimensional design, and the ability to understand and manipulate complex data structures.

• Strong background in experiment design and statistical analysis, capable of conducting and analyzing A/B and multivariate tests.

• Knowledge of Big Data technologies, preferably with experience in BigQuery and the Google Cloud Platform.

• Experience in data engineering and pipeline development, e.g., through tools like Airflow, is highly regarded.

• Familiarity with classical machine learning frameworks (e.g., Scikit-learn, XGBoost, LightGBM) is advantageous.

Qualifications:

• Bachelor's or Master's degree in Engineering, Computer Science, Technology, or related fields. An advanced degree is preferred.

• A minimum of 8+ years of experience in data science, with at least 3+ years in a leadership role managing data teams or operations.

• Proven leadership ability in managing diverse, high-performing teams and in developing and executing strategic plans to meet business objectives.

• Exceptional collaboration and communication skills, capable of guiding, influencing, and persuading a wide range of stakeholders.

• Demonstrated problem-solving skills with a growth mindset, able to tackle complex challenges and drive forward innovative solutions.

• A strong sense of ownership and accountability, coupled with a commitment to delivering high-quality results.

Who we are

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.

We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.

Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.

Role Summary

As a Senior Manager leading the Growth Data Science unit, you will play a pivotal role in leading and accelerating growth strategies across multiple dimensions, including marketing optimization and efficiency, growth product initiatives (e.g., churn reduction), ecosystem plays (e.g., subscription models and rewards), and ads revenue optimization. This leadership position will require close collaboration with product teams, senior marketing and partner growth leadership, ultimately driving data-driven decision-making and achieving transformative business growth.

You will collaborate closely with business leaders, and a dynamic team of data scientists and engineers. Your leadership will ensure the seamless integration of the data value chain—from data collection and modeling to analysis, reporting, and experimentation—ultimately empowering Talabat to achieve operational excellence and unparalleled customer satisfaction.

What’s On Your Plate?

Responsibilities:

• Lead the strategic vision for harnessing data to refine and enhance logistics operations. This involves identifying key opportunities for process optimization, cost reduction, and service quality improvements, ensuring that data science initiatives are perfectly aligned with Talabat’s broader business goals.

• Champion the adoption of a data-driven culture within logistics operations, emphasizing the importance of basing decisions on rigorous data analysis and actionable insights. This includes promoting the use of advanced analytics and data science methodologies across all levels of logistics operations.

• Build and maintain strong collaborative relationships with key stakeholders across product, business, and engineering teams. Ensure that data science projects are integrated with and supportive of overall business strategies, fostering a cohesive approach to achieving Talabat’s objectives.

• Guide, mentor, and develop a highly skilled team of data scientists and data analysts. Set clear performance goals, facilitate professional development opportunities, and foster a supportive and innovative work environment that attracts top talent.

• Spearhead innovative data science projects, including the application of predictive analytics, machine learning models, and optimization algorithms. Focus on projects that have the potential to significantly impact logistics efficiency and customer satisfaction.

• Ensure the development and maintenance of a robust and scalable data infrastructure that supports advanced analytics and data science activities. This includes advocating for best practices in data governance, quality control, and compliance with relevant data protection regulations.

• Oversee the generation of insightful analytical reports and dashboards that track key performance indicators (KPIs) and provide strategic insights to both the logistics team and senior management. Ensure that these insights are actionable and contribute to informed decision-making processes.

• Serve as a key point of communication between the data science unit and both internal and external stakeholders. Translate complex data-driven insights into clear, understandable, and actionable recommendations for various audiences.

• Stay abreast of the latest trends and advancements in data science, logistics, and technology. Incorporate cutting-edge practices and tools into Talabat’s data science strategy to maintain a competitive edge and foster continuous improvement.

• Effectively manage resources and priorities to strike a balance between long-term strategic initiatives and immediate operational needs. Ensure that the data science team’s efforts are focused on projects with the highest potential for positive impact on Talabat’s operations.

• Design, implement, and manage experimental frameworks, such as A/B testing, to validate new ideas and measure their impact on logistics performance. Use these insights to guide continuous improvement efforts.

• Provide expert analytical support to cross-functional teams, assisting in the development of KPIs and goal-setting processes that align with Talabat’s strategic objectives.

• Lead by example to cultivate an environment of excellence and innovation within the data science team. Encourage creative thinking, continuous learning, and the exploration of new ideas to drive forward Talabat’s logistics operations.

What Did We Order?

Technical Expertise:

• Proficient in the full data analysis lifecycle, including problem formulation, data auditing, rigorous analysis, interpretation, and presentation.

• Advanced skills in data analysis tools and programming languages such as Python, R, and SQL.

• Demonstrated expertise in data modeling, dimensional design, and the ability to understand and manipulate complex data structures.

• Strong background in experiment design and statistical analysis, capable of conducting and analyzing A/B and multivariate tests.

• Knowledge of Big Data technologies, preferably with experience in BigQuery and the Google Cloud Platform.

• Experience in data engineering and pipeline development, e.g., through tools like Airflow, is highly regarded.

• Familiarity with classical machine learning frameworks (e.g., Scikit-learn, XGBoost, LightGBM) is advantageous.

Qualifications:

• Bachelor's or Master's degree in Engineering, Computer Science, Technology, or related fields. An advanced degree is preferred.

• A minimum of 8+ years of experience in data science, with at least 3+ years in a leadership role managing data teams or operations.

• Proven leadership ability in managing diverse, high-performing teams and in developing and executing strategic plans to meet business objectives.

• Exceptional collaboration and communication skills, capable of guiding, influencing, and persuading a wide range of stakeholders.

• Demonstrated problem-solving skills with a growth mindset, able to tackle complex challenges and drive forward innovative solutions.

• A strong sense of ownership and accountability, coupled with a commitment to delivering high-quality results.

Since launching in Kuwait in 2004, talabat, the leading on-demand food and Q-commerce app for everyday deliveries, has been offering convenience and reliability to its customers. talabat’s local roots run deep, offering a real understanding of the needs of the communities we serve in eight countries across the region.

We harness innovative technology and knowledge to simplify everyday life for our customers, optimize operations for our restaurants and local shops, and provide our riders with reliable earning opportunities daily.

Here at talabat, we are building a high performance culture through engaged workforce and growing talent density. We're all about keeping it real and making a difference. Our 6,000+ strong talabaty are on an awesome mission to spread positive vibes. We are proud to be a multi great place to work award winner.

Principle Responsibilities & Key Results Area

• Identify innovation opportunities related to data and data processes to help clients implement fact-based decisioning within their cards and payments programs.
• Focus on transaction data modeling and analytics for cards and payments products, collaborating with Business Managers, Consultants, and Data Scientists from Visa and client organizations to co-create and deploy data-driven solutions.
• Work with regional and global Data Science teams to develop high-quality analytic products that support Visa's growth.
• Create scalable frameworks for Gen AI and ML models.
• Introduce cutting-edge tools and techniques to keep Visa at the forefront of Data Science advancements.
• Develop innovative analytic methods to address complex business challenges.
• Drive the commercialization of scalable assets such as models, dashboards, and solutions.
• Collaborate with Technology and Data Engineering teams to leverage Visa's platforms and broader ecosystem for client needs.
• Share and build global best practices and knowledge within the team.
• Promote innovative, scalable ideas with market demand.
• Ensure compliance with Model Risk Management, Visa Analytics Rules, and Global Privacy standards to maintain Visa's market reputation.
• Coordinate with Data Engineering and Data Science teams and vendors to meet business needs, ensuring quality and performance.
• Engage with VCA CEMEA Service Line Leads to identify market opportunities, gather requirements, and support go-to-market strategies.
• Work with Global Practice Leads to incorporate best practices and leverage global solutions.
• Manage relationships with external vendors and agencies, supervise deliveries, and support recruitment and onboarding.
• Develop new tools and techniques in collaboration with teams and consultants for future activities.
• Oversee project budgets and resources.
• Coordinate with internal teams like Finance, Audit, Legal, Tax, and Sourcing to optimize vendor and client engagement processes.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Qualifications :

• Minimum of 10 years of experience applying Machine Learning solutions to business problems, with production experience in model development.
• Experience using GenAI to solve business challenges.
• Postgraduate degree (Masters or PhD) in a quantitative field such as Statistics, Mathematics, Data Science, Operational Research, Computer Science, Informatics, Economics, or Engineering.
• Experience in Card & Payments markets globally, especially in payments, retail banking, or retail merchant industries.
• Strong understanding of Payments and Banking industry verticals.
• Expertise in data, market intelligence, business intelligence, and AI tools, with the ability to incorporate new techniques.
• Proven track record in commercializing analytical solutions.
• Experience managing large projects with cross-functional teams, resource planning, and delivery.
• Ability to present ideas and analyses effectively to diverse stakeholders.
• Proven results delivery within scope, timeline, and budget.
• Strong people and project management skills.

• Expertise in distributed computing environments/big data platforms (Hadoop, Elasticsearch, etc.) and database systems (SQL, Hive, HBase, etc.).
• Familiarity with Linux, Shell Scripting, and IDEs like Jupyter Notebooks.
• Strong programming skills in Python, R, Scala, SQL.
• Experience designing solution architectures with APIs and microservices.
• Knowledge of techniques like Regression, Decision Trees, Neural Networks, and others listed.
• Expertise in advanced data mining and statistical modeling techniques.

• Integrity, maturity, and a constructive approach to challenges.
• Role modeling Visa values.
• Striving for excellence and results.
• Sound judgment and decision-making aligned with business needs.
• Resource allocation across multiple business lines and geographies.
• Influencing senior management and stakeholders.
• Change management leadership.
• Fluency in English is mandatory.

Additional Information :

Visa is an EEO Employer. Qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status. Visa also considers qualified applicants with criminal histories in accordance with EEOC guidelines and applicable laws.

Remote Work : No

Employment Type : Full-time

This role supports strategic and operational decision-making across departments. It combines strong business acumen with technical proficiency in tools like Excel, SQL, Python, and Power BI.

• Data collection, cleaning, and analysis from various systems.
• Maintenance of regular performance dashboards for occupancy, revenue, collections, and expenses.
• Generation of actionable insights and data visualizations to support leadership in key decisions.
• Assistance with forecasting and scenario planning (e.g., revenue trends, cost optimization).
• Ad hoc analysis and research on market trends, competitors, and benchmarks.
• Collaboration with teams (Finance, Legal, IT, etc.) to understand business needs and validate data.
• Identification of inconsistencies or inefficiencies in data or internal workflows, and proposal of improvements.
• Support for automation of recurring reports using Excel, BI tools, SQL queries, or Python scripts.

• Bachelor's degree in a STEM field, Finance, Economics, Statistics, Business Analytics, or a related discipline.
• 2-4 years of experience in a business or data analysis role, preferably within real estate or operational functions.
• Familiarity with UAE real estate regulations is an advantage.
• Proficiency in Microsoft Excel (advanced level), SQL, and Python for data handling and automation.
• Experience with BI tools such as Power BI (or similar platforms).
• Ability to build dashboards, analyze KPIs, and explain findings to non-technical stakeholders.

• Full-time employment offers the opportunity to work with a dynamic team and contribute to the company's success.
• Employment Type: Full-time.
• Job Function: Business Development and Investment Management.

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 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.