Director - Prediction and Data

About the role:

Ezra is seeking an experienced data science and data engineering leader for our Dubai fintech team.

This role blends leadership with strong technical expertise across predictive analytics in the micro-credit and lending space. You will lead a combined team of data engineers, machine learning engineers, and prediction analysts through the full data lifecycle from raw data to production and monitoring of predictive models that deliver innovative, scalable prediction solutions that drive financial inclusion across EZRA’s markets.

Working alongside the credit risk, product and commercial teams, you will deliver innovative, scalable prediction solutions that support measurable business and revenue decisions to optimise growth within robust risk management frameworks.

This role requires a strong foundation in software engineering, machine learning, and data platforms, with the ability to think strategically while delivering production-ready systems and solutions. Experience in Fintech, credit scoring and/or mobile money / micro-lending is highly advantageous.

• Partner with Risk, Product, and Commercial teams to turn alternate datasets, modelling methodologies, automation and modelling outputs into practical market rules, portfolio strategies, limit-setting frameworks, and profitability levers.
• Through risk and affordability frameworks, and in close collaboration with Credit Risk, drive improvements in collections performance, reduce credit losses, enhance the customer lifecycle value, increase the product value proposition and support profitable scaling of Airtime Credit, Nano, Overdraft, Line of Credit, Instalment and BNPL, etc. product lines across a multitude of customer segments, i.e. consumer, agent, merchant, SMME..
• Standardise scoring pipelines, feature stores, model governance, and real-time data flows to support rapid expansion into new markets, partners, and product lines with consistent performance.
• Maintain and evolve a “champion/challenger” framework as a means to test and finetune pockets of opportunity at a market/product level, striving further towards revenue and risk optimisation.

• Design and maintain scalable machine learning systems, data pipelines, and APIs for credit decisioning.
• Optimize and expand internal codebases for model training, scoring, monitoring, and feature generation.
• Drive production deployments with high-quality, testable, and maintainable code.
• Develop and progress continuous automation and real-time capability in support of the product roadmap and evolution thereof.
• Enhance documentation, reproducibility, observability, and overall system reliability.

• Build and mentor a high-performing team across prediction analytics, machine learning engineering, and data engineering.
• Lead the prediction and data roadmap aligned with Ezra’s business expansion goals.
• Present risk insights, model performance, and strategic recommendations to executive leadership and key stakeholders.

• 12+ years operationalizing machine learning models in production environments.
• 5+ years leadership experience managing multiple technical teams.
• 6+ years writing robust, production-grade Python software (OOP, modular design).
• 6+ years designing and implementing feature stores and feature engineering workflows in SQL (Postgre
  
  SQL, Redshift, or similar) and/or Python.
• 5+ years serving ML models via RESTful APIs (e.g., FastAPI) or high-scale batch processes.
• 3+ years ML Ops experience with tools such as MLflow and Docker.
• Strong understanding of model monitoring, data quality systems, and governance.
• Strong Git experience in collaborative development environments.
• Comfortable working in Linux environments and CLI-based tooling.
• Experience with CI/CD pipelines (e.g., Bitbucket Pipelines).
• Excellent analytical, written and verbal communication skills, including the ability to explain technical concepts to non-technical teams and presenting analytical outcomes in a methodical and articulate manner.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related…