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Data Scientist-Model Validation

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Onsite

Data Scientist-Model Validation

UnionBank of the Philippines

Data Scientist-Model Validation

Skills

SQL QueriesPythonRMachine LearningComplianceRegulatory ComplianceRisk Management

10 days ago

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Important information


Contract type:

Permanent

Location:

Pasig, Metro Manila, Philippines

Work mode:

Onsite

Published on:

12 October 2026

What they need


Position Title: Data Scientist-Model Validation

Location: UnionBank Plaza, Ortigas, Pasig City

About The Role The Model Validator Officer will work with cross-functional teams to identify, assess, and mitigate risks in all mathematical and machine learning models used throughout the bank. He/she will also ensure that the models are reliable and in compliance with any relevant regulations, laws, or internal policies.

What You'll Do

  • Model Review and Validation
  • Perform independent reviews of models
  • Challenge model assumptions and results
  • Review model documentation, code, and implementation
  • Assess model conceptual soundness, data quality, and methodology
  • Validate model outputs against expected results.
  • Identify model limitations, biases, and uncertainties
  • Risk Assessment and Mitigation
  • Evaluate model risk and identify potential vulnerabilities
  • Recommend risk mitigation strategies
  • Identify areas for improvement
  • Regulatory Compliance
  • Ensure adherence to BSP regulatory and internal policy requirements
  • Comply with industry standards and best practices
  • Documentation and Reporting
  • Maintain detailed validation reports
  • Document model limitations, assumptions, and recommendations
  • Communicate validation results to model developers and business units

What We're Looking For

  • Bachelor’s degree in a quantitative field (mathematics, statistics, finance, economics, computer science)
  • Master’s degree in any relevant field is preferred
  • With at least 3 years of related experience in model validation
  • Strong analytical, statistical, and technical skills
  • Proficiency in programming languages (e.g., Python, R, SQL)
  • Knowledge of machine learning, statistics, and modeling techniques
  • Familiarity with regulatory requirements and industry standards is preferred

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