Senior Data Scientist

UMATR; Abu Dhabi; On-site; AED 420,000 - 720,000; Full time

Job summary

UMATR in Abu Dhabi is seeking an experienced data scientist to build and deploy predictive models for risk assessment, forecasting and optimisation. You will develop AI-powered workflows and orchestrate LLM-driven processes.

You will own the full model lifecycle from experimentation to deployment, monitor performance and ensure guardrails. Strong Python, SQL and ML tooling are essential, plus experience with XGBoost/LightGBM and SHAP.

Qualifications

• 6+ years of experience in data science, AI/ML or quantitative modelling.
• Production-grade experience with forecasting, regression, classification, and optimization.
• Hands-on with XGBoost or LightGBM and SHAP for model interpretation.
• Strong Python (Pandas, Scikit-learn) and SQL skills.

Responsibilities

• Build and deploy predictive models for risk assessment and forecasting.
• Develop AI workflows with guardrails and oversight.
• Orchestrate LLM-powered workflows with structured and unstructured data.
• Own full model lifecycle from experimentation to deployment and monitoring.
• Establish evaluation, versioning and monitoring practices.
• Develop model-serving APIs for scalable production systems.
• Work with large datasets to identify patterns and opportunities.
• Build dashboards translating outputs into insights.
• Collaborate with engineering and senior business stakeholders.
• Present findings clearly to technical and non-technical audiences.

Skills

Forecasting

Regression

Classification

Optimization

XGBoost

LightGBM

Python (Pandas, Scikit-learn)

SQL

MLOps

LLMs

Communication

Education

Master's degree in Data Science

Tools

Python

SQL

Pandas

Scikit-learn

Job description

Build and deploy predictive models for risk assessment forecasting classification and optimisation Develop AI-powered workflows and intelligent systems with appropriate guardrails and human oversight Build and orchestrate LLM-powered workflows combining structured and unstructured data Own the full model lifecycle from experimentation and validation through to deployment monitoring and iteration Establish robust evaluation versioning and monitoring practices to maintain model reliability Develop model-serving APIs and contribute to scalable production systems Work with large and complex datasets to identify patterns signals and opportunities for improved decision-making Build dashboards and reporting tools that translate quantitative outputs into actionable insights Partner closely with Engineering and senior business stakeholders to turn complex problems into effective data science solutions Present modelling and analytical findings clearly to technical and non-technical audiences

6+ years' experience in Data Science, Quantitative Modelling or AI/ML, with meaningful production experience. Strong experience with forecasting, regression, classification, optimisation and/or risk modelling . Hands-on experience with models such as XGBoost or LightGBM , alongside model interpretation techniques such as SHAP. Advanced Python skills, particularly Pandas and Scikit-learn. Strong SQL and experience working with relational or analytical databases. Proven experience taking ML models or AI systems from experimentation into production . Understanding of MLOps, including experiment tracking, model versioning, deployment and monitoring. Strong software engineering fundamentals and the ability to debug complex data and model pipelines. Familiarity with LLMs, AI agents and intelligent workflows . Strong communication skills and the ability to translate complex quantitative work into clear business insights.