AI Data Analyst (Predictive Intelligence & Agentic Systems)

Our client is a Dubai-based developer shaping the future of real estate and hospitality through technology-led, design-driven projects.
Their vision combines intelligent living, longevity and wellness, and autonomous systems within every development.
Operating across smart home technology, robotics and agentic AI, they are building homes that think, learn and respond.
They are assembling a high-calibre technology team to turn raw data into a truly predictive and personalised living experience.

• →Architect and maintain a high-performance Data Lake to ingest, store, and process massive streams of event data from smart home devices, sensors, and robotic units.
• →Design robust ETL/ELT pipelines to ensure data integrity, low-latency availability, and high-quality inputs for model training.
• →Implement advanced Data Vectorization and Chunking strategies to prepare unstructured data for RAG (Retrieval-Augmented Generation) and long-term agent memory.

• Develop and deploy Machine Learning models to identify behavioural patterns (e.g., user routines, occupancy trends, and environmental preferences).
• Conduct Inference Training to refine how our agents “reason” about user journeys, moving from simple triggers to complex anticipatory actions.
• Perform deep-dive Event Analysis to identify anomalies, optimise system performance, and improve the reliability of autonomous robot behaviours.

• Build the logic that powers Predictive Automation: ensuring the home doesn’t just react to a command, but anticipates the user’s next move.
• Develop “User Journey” models that allow our Agentic Interfaces to provide proactive assistance (e.g., preparing a meeting room before the user arrives or adjusting home climate based on predicted activity).
• Collaborate with the Robotics and AI Engineering teams to feed personalised “profiles” into the agentic workflows.

• Create internal dashboards to monitor the “health” of our intelligence, tracking model accuracy, prediction success rates, and data flow bottlenecks.
• Translate complex data findings into actionable product insights for the engineering and design teams.

• Data Engineering: SQL, Python (Expert), Spark/Flink, Data Lake Architecture
• Machine Learning: Scikit-learn, PyTorch/TensorFlow, Inference Optimisation, Reinforcement Learning (basics)
• Vector Databases: Pinecone, ChromaDB, or Weaviate (experience with Vectorization & Chunking)
• Data Processing: DuckDB, Apache Parquet, Pandas, NumPy
• AI Frameworks: LangChain/LangGraph (for RAG data prep), OpenAI API, Ollama
• IoT & Telemetry: MQTT, Home Assistant Data Exports, Time-Series Analysis
• Mathematics: Probability, Statistics, Linear Algebra (for model training)

• Data Science Background: A degree in Data Science, Computer Science, or a related quantitative field.
• Predictive Modeling Experience: Proven experience building models that predict human behaviour or time-series events.
• RAG Expertise: Deep understanding of how to chunk and vectorise data for Large Language Models (LLMs).
• Agentic Mindset: An understanding of how “Agents” differ from standard “Automations”, focusing on reasoning and planning rather than just If/Then logic.

You won’t be cleaning spreadsheets; you will be building the Cognitive Layer of a modern home. You will have the opportunity to work with cutting-edge data architectures and see your models directly influence how people interact with their physical environment. If you want to turn “Smart Homes” into “Intuitive Homes,” this is your role.

• Portfolio Focus: We value candidates who can demonstrate a project involving time-series prediction, a custom RAG pipeline, or a complex data visualisation of IoT telemetry.
• Scalability Mindset: As the business grows, so will our data. We need someone who thinks about how to scale data ingestion from 10 homes to 10,000.
• Privacy First: You must have a strong understanding of data privacy and how to anonymise/secure sensitive user telemetry while still maintaining high-utility data for ML training.