Staff Data Scientist

mylo is a fintech platform dedicated to helping millions of people and businesses thrive by providing accessible and responsible financial solutions. Whether you’re purchasing a mobile phone, a new jacket, a flight ticket, a comfy couch, or even covering school tuition, mylo enables you to buy now and pay later at thousands of points of sale across Egypt. Born out of B.TECH-Egypt’s leading electronics and appliances retailer with over 27 years of experience in offering buy now, pay later solutions-mylo brings a legacy of trust and innovation to the fintech space. All mylo products are fully Sharia-compliant, ensuring ethical and inclusive financial practices.

The Role We are looking for a Staff Data Scientist to lead the technical strategy for our decisioning engines. You will operate at the intersection of Data Science and Software Engineering, designing high-scale systems that power multiple business lines-from Growth & Pricing to Underwriting & Collections. You will move beyond simple model building to architecting robust, reproducible MLOps pipelines that serve real-time financial decisions.

Responsibilities

• Multi-Domain Technical Strategy: Lead the development of ML solutions across diverse contexts, ensuring that models for Credit Risk, Pricing Elasticity, and Collection Optimization utilize shared infrastructure efficiently.
• MLOps Architecture: Champion the adoption of modern Model Serving frameworks and Feature Stores. Design workflows that ensure feature consistency between training and real-time inference.
• Engineering Standards: Establish rigorous standards for Data Versioning, experiment tracking, and Hyperparameter Optimization, ensuring all research is reproducible and production-ready.
• Production Deployment: Oversee the transition of models from notebook environments to low-latency production APIs. Ensure models are wrapped, containerized, and integrated seamlessly with backend services.
• Mentorship: Guide the team in best practices for Python software engineering, including testing strategies, code structure, and performance optimization.

Requirements

Requirements

• Experience: 7+ years in Data Science with a strong emphasis on production engineering. Experience in Fintech, Lending, or Risk is highly preferred.
• ML Proficiency: Deep understanding of both classical machine learning (Gradient Boosting, Statistical Models) and Deep Learning frameworks.
• Production Engineering: Proven track record of deploying models in real-time environments. Familiarity with the concepts of Feature Stores and Model Registries is essential.
• Technical Stack: Expert-level Python skills. Strong proficiency in SQL and relational database design.
• Strategic Thinking: Ability to translate complex business KPIs (e.g., reducing Non-Performing Loans) into technical ML roadmaps.