- Company Name
- Pacific Life
- Job Title
- Advanced Analytics Director, Model Risk Management (MRM)
- Job Description
-
**Job Title:** Advanced Analytics Director, Model Risk Management (MRM)
**Role Summary:**
Lead enterprise‑wide model risk oversight for predictive, machine‑learning, and generative AI models. Define and enforce validation standards, partner with data scientists, legal, compliance and senior leadership, and embed robust governance throughout the model lifecycle.
**Expectations:**
- Conduct thorough reviews of advanced analytic models and deliver actionable recommendations to business owners and risk committees.
- Create and maintain a Generative AI model validation playbook based on emerging best practices and research.
- Serve as a trusted liaison across analytics, legal, and compliance functions, influencing model design and governance.
- Develop AI‑driven tools to improve MRM workflow efficiency and oversight quality.
- Monitor emerging technologies, tools, and regulatory changes, updating MRM and AI governance frameworks accordingly.
**Key Responsibilities:**
1. Lead comprehensive model validation assessments for predictive, ML, and generative AI models.
2. Translate validation findings into concise reports for senior leaders and risk committees.
3. Author and update enterprise standards and playbooks for AI/ML model validation.
4. Collaborate with data science teams to ensure models align with risk appetite and materiality criteria.
5. Build and implement AI solutions that automate and enhance MRM processes.
6. Provide subject‑matter expertise to legal and compliance teams on model risk issues.
7. Track industry trends, regulatory updates, and emerging tools; integrate relevant advancements into MRM practices.
**Required Skills:**
- 10+ years experience developing and validating advanced analytic models, preferably in financial services.
- Proficient in Python, SQL, and modern ML libraries (e.g., scikit‑learn, TensorFlow, PyTorch).
- Experience with cloud‑based ML pipelines and MLOps (e.g., AWS SageMaker, Azure ML, GCP AI Platform).
- Strong analytical, risk‑based thinking and ability to prioritize by materiality.
- Excellent written and verbal communication; capable of translating technical concepts for non‑technical audiences and influencing senior stakeholders.
- Self‑starter with a continuous learning mindset, especially in generative AI tools and techniques.
**Required Education & Certifications:**
- Master’s degree or Ph.D. in Statistics, Data Science, Computer Science, or a closely related field.
- Relevant professional certifications (e.g., FRM, CFA, CAMS, or AI/ML certifications) are desirable but not mandatory.