Assistant Vice President – Data Science

Lever, Inc.; Abu Dhabi; On-site; AED 420,000 - 680,000; Full time

Job summary

Lever, Inc. in Abu Dhabi seeks an AVP of Data Science to design, build, and productionize advanced analytics and AI solutions that drive measurable business value.

You will translate complex challenges into data-driven models, collaborating with data product owners, analysts, BI developers, and data quality specialists. You will leverage Python, SQL, and modern ML frameworks to develop scalable, explainable models, ensure governance, and align with organizational priorities, contributing to AI

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field.

Responsibilities

• Translate business problems into data science projects with clear hypotheses, metrics and validation.
• Explore, clean, and transform structured and unstructured data using Python and SQL.
• Design, train, and evaluate ML models using appropriate algorithms.
• Collaborate with engineering to productionize AI models via reproducible pipelines and CI/CD.
• Apply explainability, fairness, and governance techniques for transparency.
• Support AI governance activities including Model Risk Management (MRM).
• Conduct and analyze A/B tests to assess model performance and features.
• Define business outcomes with Data Product Owners and monitor model performance post-deployment.
• Collaborate with Data Quality Specialists to ensure data quality and governance.

Skills

Python

SQL

Databricks

ML frameworks

Model governance

MLOps

Communication

Education

Bachelor's degree in CS/DS/Stats

Master's degree in DS/ML (adv)

Tools

Databricks

MLflow

Airflow

Docker

Kubernetes

GitHub

APIs

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.