What Jobs are available for Marketing Data Analyst in Abu Dhabi?

Overview

PANGAIA exists to design a future where people and planet reconnect, through every product we create, the stories we tell, and every action we take. We fuse innovation, design, and purpose to responsibly deliver products and experiences that nurture well-being while ensuring minimal collective environmental footprint.

We are a global collective: one heart, many creative minds. From designers to scientists, from storytellers to retailers, we unite to build a platform that brings meaningful innovation to life. We don’t just sell products — we redefine their role: shifting from symbols of consumption to instruments for wellness, consciousness, and lasting positive impact.

Our vision is simple: empower people to live more intelligently, beautifully, and responsibly through purposeful design, cutting-edge innovation, uncompromising quality, and a deeply connected community.

We are seeking a technically skilled and detail-oriented Data & Business Analyst to be a cornerstone in building our data-driven decision-making capability.

PANGAIA is a D2C brand with most sales via its webshop, and we are now planning a significant expansion of our retail activities. Building a strong analytics backbone to support both online and offline businesses is pivotal to provide leadership with a robust data basis for strategic and operational decisions.

In the initial phase, the focus will be on data consistency across systems and departments, implementing a master data concept, and setting up a scalable analytics infrastructure and logic. Once this foundation is in place, the role will evolve into delivering advanced analytics, predictive models, and actionable insights across both e-commerce and retail operations.

• Support the rollout of a master data management concept across all systems (ERP, PLM, CRM, POS, e-commerce).
• Ensure data accuracy, consistency, and availability across D2C and retail channels.
• Design data pipelines that integrate transactional, operational, and customer data.
• Establish governance processes for data ownership, taxonomy, and hierarchy.

• Build dashboards and reports that cover both online and retail performance.
• Provide KPIs and insights for e-commerce (traffic, conversion, AOV, CAC, LTV, returns) and retail (footfall, basket size, sales per sqm, conversion rates).
• Support omni-channel analytics such as customer journey tracking across online and retail touch points.
• Monitor product performance across SKUs, categories, and geographies.

• In coordination with the commercial team on developing demand forecasting models combining internal sales data with external data (seasonality, macroeconomic trends, weather, events).
• In coordination with commercial teams, build predictive analytics for inventory planning, replenishment, and allocation across e-commerce and retail.
• Use AI/ML to create customer segmentation models, churn predictions, and personalized recommendations.
• Continuously refine and validate models to enhance decision-making quality.

• Analyse the full value chain: sourcing, logistics, fulfillment, and returns.
• Provide insights into process efficiency, lead times, and cost optimisation.
• Enable leadership to make informed decisions on pricing, promotions, and assortment strategy.
• Support finance with margin and profitability analytics across sales channels.

• Create analytics frameworks for customer service performance, NPS, and satisfaction tracking.
• Monitor omni-channel customer engagement (CRM campaigns, loyalty programs, retail events).
• Support marketing funnel optimization with data-backed insights.

• Strong command of SQL and experience with data warehouses (Snowflake, Big Query, Azure).
• Programming skills in Python or R for analysis, modelling, and machine learning.
• Experience with ETL/ELT pipelines and data integration tools (dbt, Fivetran, Airflow, Celigo).
• Proficiency with visualisation tools (Power BI, Tableau, Looker).
• Familiarity with cloud environments (Azure, AWS, GCP).
• Understanding of APIs and integrations across ERP, CRM, PLM, POS, and e-commerce platforms.

• Expertise in forecasting, predictive modelling, and machine learning.
• Strong statistical background with ability to apply regression, clustering, time-series analysis, A/B testing.
• Deep knowledge of retail and e-commerce KPIs.
• Ability to create omni-channel analytics frameworks for unified reporting.

• Experience combining online and offline data sets for holistic customer and business insights.
• Familiarity with POS data structures and retail analytics metrics (traffic counters, sales density).
• Knowledge of inventory optimization across multiple distribution channels.
• Understanding of customer behavior analytics both online (clickstream, funnels) and in-store (footfall, dwell time).
• Awareness of sustainability metrics relevant for premium fashion (returns rates, circularity, DPP readiness).

• 3–6 years of experience in data/business analytics, ideally in fashion, retail, or consumer goods.
• Hands-on problem solver with strong analytical rigor.
• Comfortable working in a fast-paced transformation environment.
• Strong communication skills — able to translate technical findings into business impact.
• Curious, proactive, and passionate about creating new capabilities.

At PANGAIA, you will play a pivotal role in building a data-driven culture and a globally recognized responsible fashion brand at scale. You’ll have the chance to work at the intersection of innovation, design, and purpose, creating impact beyond commerce while delivering meaningful returns to shareholders.

By supporting both our e-commerce core and our growing retail footprint, your work will directly shape how we scale international, grow sales and how we optimise operations.

If you are ready to shape the future of responsible fashion and lead one of our most important growth engines, we would love to hear from you.

Abu Dhabi, United Arab Emirates | Posted on 06/25/2025

We are seeking a motivated and technically sound AI & ML Analyst to support the development and deployment of machine learning models and generative AI solutions. In this role, you will work closely with senior team members to help solve real-world business problems using AI technologies and ensure smooth integration into existing systems. This is an excellent opportunity for someone with a strong foundation in machine learning, data processing, and cloud platforms to grow in a hands-on, collaborative environment.

Key Responsibilities:

Assist in building and validating machine learning models and generative AI solutions for business use cases.

Support the creation and maintenance of scalable ML pipelines, including data preparation, feature engineering, training, and evaluation.

Collaborate with senior data scientists and engineers to fine-tune models for performance and reliability in production environments.

Help integrate ML models into applications through APIs and system interfaces.

Monitor deployed models for accuracy, performance, and data quality; escalate issues as needed.

Contribute to ongoing research and benchmarking of AI tools and models to improve current solutions.

Work with data engineers to ensure high-quality data ingestion and transformation pipelines.

Learn and apply version control and CI/CD practices in the ML lifecycle using tools like Git and Azure DevOps.

Use Azure services (e.g., Azure Machine Learning Studio, Databricks) to assist with model development, testing, and deployment.

Follow best practices in documentation, code quality, and reproducibility in AI/ML projects.

Bachelor’s or Master’s degree in ComputerScience, Data Science, Engineering, or a related field.2–4 years of hands-onexperience in machine learning or data science projects.

Proficiency in Python and common ML libraries(e.g., scikit-learn, pandas, TensorFlow, PyTorch).

Exposure to cloud environments, ideallyMicrosoft Azure or similar platforms.

Familiarity with ML workflows, versioncontrol, and basic DevOps practices.

Strong analytical and problem-solving skills.

Willingness to learn and collaborate acrossteams.