AVP- Data Scientist

First Abu Dhabi Bank; Abu Dhabi; On-site; AED 300,000 - 600,000; Full time

Job summary

First Abu Dhabi Bank seeks an experienced Senior Data Scientist to design and operationalize analytics products for personal banking. You will build production ML models, drive MLOps, and communicate insights to executives.

Join a collaborative team focusing on scalable data products, feature engineering, and governance, delivering measurable business value in a regulated banking environment.

Qualifications

• 5+ years of applied data science experience in banking
• Experience deploying production-grade models with ongoing performance management
• Strong skills in SQL, Python and ML libraries (scikit-learn, XGBoost)
• Experience with feature engineering and large-scale data handling
• Familiarity with MLOps pipelines and monitoring
• Strong business acumen and stakeholder engagement
• Understanding model governance and regulatory expectations

Responsibilities

• Design and build machine learning models for personal banking priorities.
• Identify viable use cases with product marketing and business stakeholders.
• Drive scalable, measurable analytics products with robust delivery.
• Build production models and deploy into production environments.
• Monitor performance and retrain or recalibrate as needed.
• Implement CI/CD pipelines and automated monitoring for models.
• Lead data exploration and feature engineering on banking data.
• Present results to senior stakeholders and translate into initiatives.

Skills

SQL

Python

ML libraries

Model deployment

Stakeholder communication

MLOps

Education

Bachelor's or Master's in quantitative field

Tools

Dataiku

Databricks

Job description

1. Advanced Analytics Product Development

• Design and build machine learning models aligned to core personal banking priorities
• Identify commercially viable use cases in collaboration with product marketing and business stakeholders
• Drive the development of analytics products that are scalable measurable and operationally robust

2. Model Development and Lifecycle Management

• Build test and deploy machine learning models into production environments
• Ensure models are aligned with Model Risk Management standards and delivery governance
• Monitor model performance and lead retraining or recalibration processes as needed

3. MLOps and Operationalisation

• Implement production-ready model pipelines using CI/CD tooling and automated monitoring
• Ensure continuity of performance and data integrity throughout the lifecycle

4. Feature Engineering and Data Exploration

• Lead the extraction and transformation of raw data into high-quality features
• Conduct deep EDA to identify trends correlations and value-driving insights
• Understand and navigate complex banking datasets including transactional behavioural and product data

5. Business Engagement and Communication

• Present modelling outcomes and insights to senior non-technical stakeholders with clarity and precision
• Translate business opportunities into concrete data science initiatives
• Provide clear recommendations and options based on data-driven insights

6. Innovation and Delivery Focus

• Develop and prototype new modelling techniques and innovative data products with a commercial lens
• Prioritise delivery and measurable value over theoretical perfection

Contribute to the development of reusable frameworks and accelerators to optimise delivery methodologies for data science teams

Qualifications :

Required Experience and Skills:

• 5 years of applied data science experience in a banking environment
• Proven track record of deploying production-grade models with ongoing performance management
• Strong hands-on skills in SQL Python and ML libraries (e.g. scikit-learn XGBoost)
• Demonstrated experience in feature engineering and large-scale data handling
• Familiarity with MLOps pipelines and tooling for monitoring and automation
• Strong commercial acumen and ability to scope and deliver high-impact use cases
• Excellent presentation communication and stakeholder engagement skills
• Deep understanding of model governance standards and regulatory expectations

Preferred Qualifications:

• Experience with platforms such as Dataiku and Databricks is a significant bonus
• Strong Retail banking domain knowledge
• Proven experience with statistical modelling mastery
• Bachelors or Masters degree in a quantitative field (e.g. Computer Science Statistics Engineering)

Experience working in cloud environments (Azure AWS or GCP)

Remote Work :

No

Employment Type :

Full-time