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3 часа назад

Quantitative Analytics Manager – Model Risk Management

Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Текст:
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TL;DR
Quantitative Analytics Manager – Model Risk Management (Machine Learning/Consumer Finance): Leading model governance and independent challenge across the lifecycle of machine learning and loss forecasting models supporting consumer lending, with an accent on statistical analysis, regulatory readiness, and analytical risk controls. Focus on validating model methodology, monitoring model performance, evaluating XGBoost-based models, and communicating defensible findings to stakeholders, auditors, and regulators.

Location: Wilmington, Delaware, United States; hybrid

Company

hirify.global provides personal loans, credit cards, and automotive lending products focused on responsible access to credit for nonprime customers.

What you will do

  • Lead model governance oversight across development, implementation, validation, use, and monitoring of machine learning models.
  • Perform independent challenge of model data, methodology, assumptions, limitations, development decisions, and performance metrics.
  • Oversee loss forecasting models and conduct periodic model validations, including benchmarking, outcomes analysis, and sensitivity testing.
  • Monitor model performance and behavior, identify emerging risks, and recommend remediation or model enhancements.
  • Partner with data science and technology teams on artificial intelligence and advanced analytics initiatives with embedded governance controls.
  • Apply regression, classification, and related statistical techniques to support risk decisions and regulatory communications.

Requirements

  • Master’s degree in Statistics, Mathematics, Data Science, or another quantitative discipline; PhD preferred.
  • 5+ years of experience in statistics, data science, decision science, or a related quantitative field.
  • 3+ years of experience building, reviewing, or validating machine learning models in consumer finance.
  • Strong understanding of consumer lending, credit risk practices, and model risk management regulations.
  • Hands-on experience with machine learning, particularly tree-based models such as XGBoost, plus proficiency in Python and SQL.
  • Ability to lead complex projects, exercise structured analytical judgment, and explain technical concepts to non-technical stakeholders, auditors, and regulators.

Nice to have

  • Experience with analytical fair lending models and analysis.
  • Experience with AWS and SageMaker.
  • PhD in a quantitative discipline.

Culture & Benefits

  • Flexible work arrangements and an inclusive, collaborative environment.
  • Medical, prescription, dental, vision, hearing, accident, hospital indemnity, and life insurance options.
  • Up to 4% matching 401(k) and an employee stock purchase plan with a 10% share discount.
  • Tuition reimbursement, paid vacation, personal days, sick leave, holidays, and volunteer time.

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