Data Scientist

Apparel Group; United Arab Emirates; On-site; AED 150,000 - 250,000; Full time

Job summary

A leading fashion retail conglomerate in the United Arab Emirates is seeking an experienced AI and ML professional to optimize inventory and pricing strategies through advanced modeling. The ideal candidate will have a strong background in data science, familiarity with LLMs, and excellent communication skills. This role offers the opportunity to work on impactful projects in a collaborative team environment.

Benefits

Collaborative work environment

Opportunity to work on innovative projects

Impact-driven team

Qualifications

• 3–5 years of experience in applied data science, ideally within retail or e-commerce sectors.
• Expertise in supervised, unsupervised, and deep learning techniques.
• Strong experience with time series forecasting and optimization modeling.

Responsibilities

• Partner with internal stakeholders to apply ML and agent-based intelligence.
• Design and deploy Demand Forecasting and Price Elasticity models.
• Build Customer Lifetime Value and Churn Prediction models.

Skills

Applied data science experience

ML and deep learning techniques

Time series forecasting

Feature engineering

Python proficiency

Communication skills

Education

Master’s or PhD in Statistics, Computer Science, Applied Mathematics

Tools

Python

PySpark

SQL

TensorFlow

PyTorch

Job description

Key Responsibilities

Business-Centric AI & Modeling

• Partner with internal stakeholders (Brand Marketing, Merchandising, CRM, and Business Strategy teams) to identify opportunities to apply ML, LLMs, and agent-based intelligence for high-value retail use cases.
• Design, develop, and deploy advanced Demand Forecasting, Markdown Optimization, and Price Elasticity models to optimize inventory and pricing strategy.
• Build and operationalize Customer Lifetime Value (CLTV), Churn Prediction, and RFM segmentation models for personalized marketing and retention strategy.
• Develop Market Basket Analysis, Cross-Sell / Recommender Systems, and Promotion Effectiveness frameworks using both classical ML and deep learning approaches.
• Create and maintain Agentic AI workflows for campaign orchestration, customer service automation, and marketing optimization (e.g., autonomous agents for A/B test selection or personalized product recommendations).

Advanced AI & Generative Intelligence

• Fine-tune Small and Large Language Models (e.g., LLaMA, Mistral, GPT, Claude) for tasks such as customer sentiment analysis, product description enrichment, and insight summarization.
• Design retrieval-augmented generation (RAG) pipelines integrating structured and unstructured data (CRM, catalog, social, and web data).
• Experiment with Agentic AI frameworks (LangChain, CrewAI, AutoGen, OpenDevin) to build multi-agent systems that can autonomously gather insights, recommend actions, or run simulations.
• Apply multimodal models (text + image) for fashion tagging, trend analysis, and visual recommendation.

MLOps, Engineering, and Deployment

• Partner with the Data Engineering and MLOps teams to productionize models at scale via CI/CD pipelines.
• Develop scalable APIs and deploy models into cloud environments (Azure, AWS, or GCP).
• Build robust monitoring frameworks for model drift, bias detection, and performance tracking.
• Contribute to development of internal AI/ML model registry and experimentation frameworks.

Qualifications

Core Data Science & ML

• 3–5 years of experience in applied data science, ideally within retail or e-commerce sectors.
• Expertise in supervised, unsupervised, and deep learning techniques (Regression, Random Forest, XGBoost, LightGBM, ARIMA, SARIMAX, GARCH, CNNs, RNNs, Transformers).
• Strong experience with time series forecasting, optimization modeling, and causal inference.
• Experience with feature engineering, model tuning, and validation at scale.

LLM, SLM & Agentic AI Exposure

• Experience fine-tuning or prompt-engineering LLMs for enterprise tasks (e.g., summarization, insight generation, or dialogue systems).
• Familiarity with LangChain, LlamaIndex, or CrewAI for developing autonomous or semi-autonomous agents.
• Understanding of retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, Weaviate), and embedding models.
• Experience leveraging multimodal AI (vision + language) for product recommendations or catalog enrichment.

Programming & Tools

• Advanced proficiency in Python, PySpark, and SQL.
• Experience with TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, and LLM APIs.
• Exposure to any of the MLOps frameworks (MLflow, Kubeflow, Airflow, Vertex AI, SageMaker).
• Comfortable with distributed computing tools (Spark, Hadoop, Hive) and data lakes (Databricks, Delta Lake).

Business & Communication

• Proven ability to translate complex data insights into business strategy.
• Experience collaborating with non-technical stakeholders in retail, marketing, and merchandising domains.
• Excellent written and verbal communication skills.

Preferred

• Master’s or PhD in Statistics, Computer Science, Applied Mathematics, or related field.
• Exposure to fashion retail analytics, customer behavior modeling, and omnichannel data systems.
• Familiarity with Web Analytics tools (Google Analytics, Adobe Analytics) and APIs (Google Maps, Geocoding).

Why Join Us

• Shape the future of AI-led decisioning in one of the region’s largest fashion retail conglomerates.
• Work on real-world generative and agentic AI projects beyond prototypes.
• Be part of a collaborative, innovative, and impact-driven Data Science & AI team.