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AI Developer (Financial)

SM North EDSA Tower 1
AI Developer (Financial)
Full Time
From ₱200,000 per month

Job Description

  • Develop and deploy AI and machine learning models for loan eligibility, risk scoring, fraud prevention, and default prediction specific to short-term lending operations.
  • Analyze large volumes of customer and transactional data to uncover insights that optimize underwriting and repayment processes.
  • Collaborate with finance, risk, and operations teams to identify automation and predictive opportunities within the cash advance workflow.
  • Integrate AI-driven decisioning into loan management systems and CRM tools.
  • Build and refine predictive models to ensure compliance with US lending regulations and company policies.
  • Continuously monitor, test, and retrain AI models to maintain accuracy and reduce bias in lending decisions.
  • Document AI models and data pipelines, ensuring transparency and auditability in line with financial compliance requirements.
  • Evaluate and implement emerging AI technologies that can enhance fraud detection, KYC validation, and credit risk assessment.


Skills and Qualifications

  • Bachelor’s or master’s degree Computer Science, Artificial Intelligence, Data Science, or Financial Engineering.
  • 3+ years of experience in AI or machine learning, preferably within consumer lending, fintech, or financial services.
  • Strong programming skills in Python, R, or Java, with hands-on experience using TensorFlow, PyTorch, or scikit-learn.
  • Solid understanding of credit risk modeling, loan underwriting, and financial data structures.
  • Experience with data visualization and analytics tools (e.g., Power BI, Tableau, or Matplotlib).
  • Familiarity with US financial regulations, data privacy standards, and ethical AI practices.
  • Excellent analytical, problem-solving, and communication skills.


Requeriments

  • Experience in US Cash Advance, payday loans, or small-dollar lending operations.
  • Knowledge of fraud analyticsidentity verification AI, and automated decisioning systems.
  • Familiarity with NLP for customer service chatbots or sentiment analysis in collections.
  • Experience in deploying AI models in cloud environments (AWS, Azure, or GCP).

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