Aldar Properties

Real estate development and asset management

Assistant Vice President - Data Science

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeAbu Dhabi - United Arab EmiratesNo salary listedIn-person

About the Job

Requirements

At least 6 years of experience in data science, applied machine learning, or advanced analytics.
Proven experience delivering models deployed and integrated into business processes or digital products.
Experience working in agile, cross-functional teams with Product Owners, Data Analysts, and Data Engineers.
Advanced proficiency in Python, including pandas, NumPy, scikit-learn, XGBoost, and LightGBM.
Strong command of SQL for data extraction, transformation, and validation.
Experience working in Databricks or equivalent data and machine learning platforms.
Familiarity with deep learning frameworks such as PyTorch and TensorFlow, and machine learning lifecycle tools such as MLflow, Airflow, Docker, and Kubernetes.
Understanding of model explainability, ethics, fairness, and governance.
Knowledge of AI governance processes and documentation standards, including Model Risk Management.
Exposure to cloud platforms such as Azure and Snowflake, and APIs for integrating AI models into applications.
Familiarity with version control using Git/GitHub and collaborative coding practices.
Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.

Responsibilities

Translate business problems into data science projects by defining hypotheses, success metrics, and validation methods.
Explore, clean, and transform structured and unstructured data using Python and SQL to prepare datasets for modeling.
Design, train, and evaluate machine learning models using appropriate algorithms and statistical techniques, including regression, classification, clustering, natural language processing, and forecasting.
Collaborate with engineering and platform teams to productionize AI models through reproducible pipelines and continuous integration/continuous delivery workflows.
Apply model explainability, fairness, and interpretability techniques, including SHAP, LIME, and feature importance, to ensure transparency and accountability.
Support AI governance activities, including Model Risk Management processes, ensuring compliance and responsible AI use.
Conduct and analyze A/B tests or controlled experiments to assess model and feature performance.
Work with Data Product Owners to define business outcomes, monitor model performance after deployment, and ensure continued relevance.
Collaborate with Data Quality Specialists to ensure input data meets quality, lineage, and governance standards.
Communicate results through visualizations, storytelling, and presentations tailored to technical and non-technical audiences.

Desired Qualifications

A master's degree or higher in Data Science, Machine Learning, or Applied Statistics is advantageous.

JOB PURPOSE

As an AVP– Data Science, you will design, build, and productionize advanced analytics and AI solutions that drive measurable business value. You will work closely with Data Product Owners, Data Analysts, BI Developers, and Data Quality Specialists to translate complex business challenges into data-driven models and experiments. Leveraging Python, SQL, and modern ML frameworks, you will develop scalable machine learning solutions that are explainable, governed, and aligned with organizational priorities.

ROLES AND RESPONSIBILITIES

Translate business problems into data science projects by defining clear hypotheses, success metrics, and validation methods.

Explore, clean, and transform structured and unstructured data using Python and SQL to prepare high-quality datasets for modeling.

Design, train, and evaluate machine learning models using appropriate algorithms and statistical techniques (e.g., regression, classification, clustering, NLP, forecasting).

Collaborate with engineering and platform teams to productionize AI models through reproducible pipelines and CI/CD workflows.

Apply model explainability, fairness, and interpretability techniques (e.g., SHAP, LIME, feature importance) to ensure transparency and accountability.

Support AI governance activities, including Model Risk Management (MRM) processes, ensuring compliance and responsible use of AI.

Conduct and analyze A/B tests or controlled experiments to assess model and feature performance.

Work with Data Product Owners to define business outcomes, monitor model performance post-deployment, and ensure continued relevance.

Collaborate with Data Quality Specialists to ensure input data meets quality, lineage, and governance standards.

Communicate results effectively through visualizations, storytelling, and presentations tailored to technical and non-technical audiences.

RELATED YEARS OF EXPERIENCE

6+ years of experience in data science, applied machine learning, or advanced analytics.

Proven experience delivering models that have been deployed and integrated into business processes or digital products.

Experience working in agile, cross-functional teams with Product Owners, Data Analysts, and Data Engineers.

FIELD OF EXPERIENCE

Analytics, Data Science, Artificial Intelligence

TECHNICAL AND INTERPERSONAL SKILLS

Advanced proficiency in Python (pandas, NumPy, scikit-learn, XGBoost, LightGBM).

Strong command of SQL for data extraction, transformation, and validation.

Experience working in Databricks or equivalent data and ML platforms.

Familiarity with deep learning frameworks (PyTorch, TensorFlow) and ML lifecycle tools (MLflow, Airflow, Docker, Kubernetes).

Understanding of model explainability, ethics, fairness, and governance.

Knowledge of AI governance processes and documentation standards, including Model Risk Management (MRM).

Exposure to cloud platforms (Azure, Snowflake) and APIs for integrating AI models into applications.

Familiarity with version control (Git/GitHub) and collaborative coding practices.

Excellent communication skills to explain technical findings in clear business terms.

Collaborative and curious, with a passion for continuous learning and innovation

QUALIFICATION

Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.

Master’s degree or higher in Data Science, Machine Learning, or Applied Statistics is an advantage.

About the Company

Aldar Properties

Real estate development and asset management

Aldar Properties is a real estate developer and asset manager in Abu Dhabi. It operates two segments: Aldar Development, which builds and sells land, homes, and commercial spaces (such as Yas Island and Saadiyat Island), and Aldar Investment, which owns and manages rental and income-generating assets like Yas Mall, offices, residences, and hotels. The company earns from property sales and from ongoing rental and asset income, relying on a mix of development projects and a steady income portfolio. Its goal is to shape Abu Dhabi’s urban landscape with large, long-term projects while expanding its asset base and regional footprint.

Company size: 5,001-10,000
Company stage: IPO
Headquarters: Abu Dhabi, United Arab Emirates
Founded: 2004

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