Data Scientist - Advanced Analytics

Majid Al Futtaim; Dubai; On-site; AED 223,200 - 334,800; Full time

Job summary

Majid Al Futtaim is seeking a Data Scientist - Advanced Analytics based in Dubai, UAE. The role involves applying machine learning and advanced analytics to transform business data into actionable insights, enhancing decision-making across various departments.

The ideal candidate will have experience in model development, proficiency in Python or R, and a strong analytical background. This position provides opportunities to work on significant business challenges and support innovation within the organization.

Qualifications

• 5-8 years of experience in data science, machine learning, applied analytics, or AI solution development.
• Strong proficiency in Python or R for model development and automation.
• Fluency in SQL or PySpark for data manipulation.

Responsibilities

• Design, build, train, and validate predictive models.
• Analyze large datasets to identify business patterns and trends.
• Collaborate with data engineers to ensure data quality and pipeline support.

Skills

Data science

Machine learning

Statistical modeling

Predictive modeling

Prescriptive analytics

Python

R

SQL

PySpark

Education

Bachelor's or master's degree in data science, statistics, applied mathematics, computer science, or related field

PhD or equivalent experience

Tools

MLOps

ETL processes

APIs

Generative AI

NLP frameworks

Job description

Role Overview

Data Scientist - Advanced Analytics in Dubai, United Arab Emirates is a strategic Retail technology role focused on machine learning, advanced analytics, predictive modeling, prescriptive analytics, MLOps, AI-enabled solutions, and data-driven business decision-making for Majid Al Futtaim Holding. The role is responsible for transforming complex business data into actionable insights while developing scalable models that support performance improvement, decision automation, and strategic business outcomes.

Role Context

The Data Scientist will manage the full model lifecycle, from data exploration, statistical analysis, feature engineering, and model development to deployment, monitoring, retraining, and continuous improvement. This role requires strong technical expertise in Python or R, SQL or PySpark, statistical modeling, machine learning, time-series forecasting, and applied analytics, with the ability to collaborate across data engineering, platform, ML engineering, strategy, and business teams.

Key Responsibilities

• Design, build, train, test, and validate predictive and prescriptive models using statistical methods, machine learning techniques, optimization models, and advanced analytics approaches.
• Analyze large and complex datasets to identify business patterns, performance drivers, customer behavior trends, operational gaps, and growth opportunities.
• Perform variance attribution, root-cause analysis, and performance diagnostics to explain deviations and recommend improvement actions.
• Develop machine learning solutions that support forecasting, classification, segmentation, recommendation, optimization, anomaly detection, and decision support use cases.
• Deploy AI-enabled solutions to streamline analytical workflows, improve productivity, and accelerate data-driven decision-making processes.
• Work closely with data engineers to ensure data pipelines, feature stores, ETL processes, and data quality checks support modeling requirements.
• Collaborate with platform and ML engineering teams to operationalize models in production through automated pipelines, APIs, monitoring tools, and scalable deployment practices.
• Implement MLOps frameworks covering model version control, documentation, reproducibility, performance monitoring, retraining triggers, governance, and lifecycle management.
• Build reusable analytical assets, model templates, accelerators, code libraries, and best-practice frameworks to improve time-to-value across data science projects.
• Translate technical model outputs into clear business insights, recommendations, dashboards, presentations, and stakeholder-ready narratives.
• Support analytical literacy across the organization by explaining data science methods, model results, limitations, and decision impact to non-technical stakeholders.
• Evaluate emerging AI, machine learning, generative AI, and NLP tools to identify practical opportunities for business use cases.
• Contribute to internal knowledge repositories, documentation standards, experimentation guidelines, and data science governance practices.
• Ensure analytical solutions are accurate, explainable, reliable, scalable, and aligned with business strategy, data governance, and responsible AI expectations.

Ideal Profile / Qualifications

• Bachelor's or master's degree in data science, statistics, applied mathematics, computer science, engineering, or a related field.
• PhD is preferred, or equivalent experience demonstrating advanced research capability and applied modeling depth.
• 5-8 years of experience in data science, machine learning, applied analytics, advanced statistics, or AI solution development within a complex or large-scale organization.
• Strong proficiency in Python or R for statistical analysis, machine learning, model development, experimentation, and automation.
• Fluency in SQL or PySpark for data extraction, transformation, feature preparation, and large-scale data manipulation.
• Deep understanding of statistical methods, regression modeling, time-series forecasting, supervised learning, unsupervised learning, model validation, and optimization techniques.
• Practical experience deploying models into production environments and working with automated pipelines, APIs, feature stores, and MLOps practices.
• Experience with model monitoring, performance drift detection, documentation, reproducibility, version control, and retraining workflows.
• Strong analytical thinking with the ability to perform root-cause analysis and convert complex data into practical business recommendations.
• Experience with generative AI or NLP frameworks such as Claude Sonnet, OpenAI APIs, Hugging Face, or LangChain is an advantage.
• Strong communication skills with the ability to explain modeling decisions, assumptions, trade-offs, and business impact to technical and non-technical audiences.
• Ability to collaborate with data engineering, ML engineering, platform, strategy, product, finance, operations, and business stakeholders.
• Results-driven mindset with strong ownership, curiosity, problem-solving ability, and commitment to high-quality analytical delivery.

Skills Set

• Data science
• Advanced analytics
• Machine learning
• Predictive modeling
• Prescriptive analytics
• Statistical modeling
• Time-series forecasting
• Regression modeling
• Supervised learning
• Unsupervised learning
• Optimization techniques
• Variance attribution
• Root-cause analysis
• Feature engineering
• Model validation
• Model deployment
• MLOps
• Model monitoring
• Model retraining
• Version control
• Python
• R
• SQL
• PySpark
• ETL processes
• Data pipelines
• Feature stores
• APIs
• AI-enabled solutions
• Generative AI
• NLP frameworks
• OpenAI APIs
• Hugging Face
• LangChain
• Business insights
• Data-driven decision-making
• Analytical literacy
• Reusable analytics assets

Why Join Us

This opportunity is ideal for an experienced Data Scientist who wants to apply advanced analytics, machine learning, and AI to strategic business challenges within a major regional group in Dubai. The role offers exposure to large-scale data environments, enterprise decision-making, model deployment, MLOps practices, generative AI opportunities, and cross-functional collaboration with teams focused on innovation, customer value, and business performance.

About the Company

Majid Al Futtaim is a leading regional business group known for creating memorable retail, lifestyle, shopping mall, leisure, entertainment, hospitality, technology, and customer-focused experiences across the Middle East, Africa, and Asia. Majid Al Futtaim Holding supports group-wide strategy, innovation, governance, digital transformation, and business excellence, helping the organization build future-ready capabilities and data-driven solutions across Dubai, the UAE, and the wider region.