AI Data Analyst (Predictive Intelligence & Agentic Systems)

Role overview

Data engineering and RAG

• Architect and maintain a data lake for device, sensor, and robot event streams.
• Build robust ETL/ELT pipelines for data integrity, low latency, and model-training quality.
• Vectorize and chunk unstructured data for RAG and long-term agent memory.

Modeling and predictive intelligence

• Develop machine-learning models for routines, occupancy, and environmental preferences.
• Refine agent inference about user journeys and enable anticipatory actions.
• Analyze events and anomalies to improve system performance and robot reliability.
• Build predictive automation and user-journey models for proactive assistance.
• Work with robotics and AI teams to feed personalized profiles into agentic workflows.

Analytics and visualization

• Build dashboards tracking model accuracy, prediction success, data flow, and bottlenecks.
• Translate findings into product insights for engineering and design teams.

Technical requirements

• Expert Python and SQL; experience with Spark or Flink and data lake architecture.
• Machine learning with Scikit-learn and PyTorch or TensorFlow; inference optimization and basic reinforcement learning.
• Pinecone, ChromaDB, or Weaviate experience, including vectorization and chunking.
• DuckDB, Apache Parquet, Pandas, and NumPy.
• LangChain or LangGraph, OpenAI API, and Ollama for RAG data preparation.
• MQTT, Home Assistant data exports, and time-series analysis.
• Probability, statistics, and linear algebra for model training.

Preferred qualifications

• A degree in Data Science, Computer Science, or a related quantitative field is preferred.
• Predictive modeling of human behavior or time-series events is preferred.
• RAG chunking and vectorization expertise and an understanding of agentic reasoning and planning are preferred.

Additional candidate guidance

Compensation and benefits

• Competitive tax-free monthly salary in AED, commensurate with experience.
• Performance incentives, UAE visa sponsorship, medical insurance, paid leave, annual flight ticket, and end-of-service gratuity.
• Modern hardware and cloud data and machine-learning tools; certification and conference support; opportunity to shape the intelligence layer.