Assistant Vice President – Data Science

Aldar; Abu Dhabi; On-site; AED 350,000 - 600,000; Full time

Job summary

Aldar is seeking an AVP – Data Science to design and productionize advanced analytics and AI solutions that drive measurable business value. You will collaborate with Data Product Owners, Analysts, BI developers and Data Quality specialists to translate challenges into data-driven models.

Using Python, SQL, and leading ML frameworks, you will build scalable, explainable models with strong governance, and contribute to MRM processes while delivering results in agile, cross-functional teams.

Qualifications

• 6+ years of experience in data science or applied ML.
• Experience delivering models deployed into business processes.
• Experience in agile, cross-functional teams.

Responsibilities

• Translate business problems into data science projects with clear hypotheses.
• Prepare high-quality datasets using Python and SQL.
• Design, train, and evaluate ML models with appropriate algorithms.
• Productionize models via reproducible pipelines and CI/CD.
• Apply explainability, fairness, and governance techniques.
• Support Model Risk Management and governance activities.
• Run A/B tests to assess model performance.
• Collaborate with Data Product Owners to define outcomes.
• Ensure data quality and governance with Data Quality Specialists.
• Communicate results with visuals and storytelling.

Skills

Python

SQL

ML frameworks

Databricks

PyTorch

TensorFlow

Explainability

AI governance

MLOps

Cloud Azure

Git

Communication

Agile teams

Data visualization

Education

Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering

Master’s degree in Data Science or related field

Tools

MLflow

Airflow

Docker

Kubernetes

GitHub

Snowflake

Azure

Job description

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.