mylo

Fintech

SeniorDataEngineer

$750–1200k ~AI est. New Cairo City, Cairo Governorate, Egypt
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Data Engineer at mylo. Skills: ML solutions, MLOps Architecture, Production deployment. Lead ML solutions development. Design MLOps workflows”

Industry & Context.

Fintech

What They're Looking For.

Must Have

4+ years in Data Science, Expert-level Python skills, Proficiency in SQL

Nice to Have

Experience in Fintech, Experience in Lending, Experience in Risk

What You'll Do.

Lead ML solutions development

Design MLOps workflows

Establish Data Versioning standards

Optimize Hyperparameter

Oversee model transition

Integrate models with services

Guide team on Python best practices

Full Job Description

**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. We are seeking a passionate and experienced **Senior Data Engineer** to join our team within the Fintech domain. This role is ideal for someone who thrives in a fast-paced environment and is excited to design, build, and scale secure, high-performing infrastructure to support a range of financial products. 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** * **Experience:**

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