Data Engineer/ML Engineer – Credit Decision Engine (Contract)

Posted 11 Days Ago
Be an Early Applicant
KSA
Mid level
Business Intelligence • Consulting
The Role
The Data Engineer/ML Engineer will build and optimize lightweight data pipelines, deploy basic model infrastructure, set up cloud environments using Google Cloud, and ensure compliance with data security standards for a credit decision engine prototype.
Summary Generated by Built In

Position: Data Engineer/ML Engineer – Credit Decision Engine

Location: Saudi Arabia/Remote

Type: Contract/Short-term

About Us:
We are a venture studio developing an open banking-powered credit decision engine that will serve as a core solution for lending platforms across Saudi Arabia. Our mission is to transform credit accessibility and decision-making in the Saudi market by leveraging real-time open banking data and advanced analytics, providing a streamlined, compliant, and data-driven approach to credit assessment.

Role Overview:
This engineer will be responsible for setting up lightweight, scalable infrastructure to support a prototype credit engine. They will design the basic data pipelines, integrate open banking data, and ensure that models can be easily deployed, tested, and iterated. The focus will be on achieving an efficient prototype setup without extensive production-level systems.

Key Responsibilities:

  1. Build Lightweight Data Pipelines:
    • Develop essential data pipelines to ingest, clean, and process open banking data, focusing on simplicity and speed for rapid prototype testing.
    • Ensure data flows securely from source to model, with a focus on handling core data points such as income and transaction history.
  2. Deploy Basic Model Infrastructure:
    • Collaborate with credit expert to set up and test models within the prototype environment, providing a simple deployment pipeline for easy model updates.
    • Create basic APIs or microservices for model access, enabling smooth communication between the model and other system components.
  3. Infrastructure Setup and Optimization:
    • Set up a lightweight, cost-effective cloud infrastructure (using Google Cloud) that meets the minimal requirements for prototype testing.
    • Implement basic monitoring to track model performance and detect issues quickly, focusing on the flexibility needed for iterative testing.
  4. Data Security and Compliance Basics:
    • Ensure that data handling adheres to basic compliance and privacy standards, focusing on secure data transfer and storage.
    • Implement essential access controls and document processes for regulatory visibility, meeting minimum viable standards in alignment with SAMA guidelines.
  5. Documentation and Collaboration:
    • Document the architecture, data flows, and model integration processes, creating a clear reference for future development and iteration.
    • Work closely with the team to ensure the prototype meets initial functionality goals and supports rapid experimentation.

Qualifications:

  • Bachelor’s degree in Computer Science, Data Engineering, or a related field.
  • 3+ years of experience as a Data Engineer, ML Engineer, or similar role, with expertise in creating simple, scalable data infrastructures.
  • Proficiency in cloud platforms (Google Cloud) and familiarity with model deployment tools.
  • Experience with building and managing data pipelines, especially for prototypes or MVPs.
  • Basic knowledge of security and compliance standards, particularly as they relate to financial data.
  • Strong problem-solving skills and the ability to work flexibly within a rapidly evolving prototype environment.

Top Skills

Data Engineering
Machine Learning
The Company
London
97 Employees
On-site Workplace
Year Founded: 2016

What We Do

Stryber is the strategic growth partner and expert in venture building. Together with our clients, we find the right innovation to successfully digitalize business models and create sustainable growth. We are passionate entrepreneurs, razor-sharp analysts, marketing & product professionals, united by one goal: to build the business behind all the ideas

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