Model Governance / Model Risk Delivery Lead

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We need to parse the posting. Job Title: Model Governance / Model Risk Delivery Lead (do not repeat as heading). Location: Charlotte, NC. Duration: Contract - 15 months (potential contract-to-hire). Pay Range: $64.52/hr (W2). Job ID: 410404 (ignore). About BCforward: description of company (maybe "About the role"? Actually "About BCforward" is about company, not role. The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content. We have "Job Description" paragraph describing role. That could go under "About the role". Then "Responsibilities:" list. Then "Required Skills & Qualifications:" which includes both skills and qualifications. We can split into Requirements (maybe required qualifications) and Skills (technical). Also "Preferred Skills:" separate. We have "Role Logistics & Interview Process:" includes start date, hybrid schedule, location approval, interview process, sponsorship. This includes schedule (hybrid schedule with minimum 3 days onsite per week). Also start date maybe not needed. Pay we have. Benefits: "Why BCforward?" bullet list includes Competitive compensation and benefits, Opportunities for growth..., supportive culture, Exposure to cutting-edge technologies. That's benefits. We need to avoid boilerplate: equal opportunity, apply now, etc. We need to preserve all substantive info. Let's extract: About the role: The paragraph after Job Description: "We are seeking a Model Governance / Model Risk Delivery Lead to join our dynamic team supporting Bank of America's Erica, Chat, and Voice Technology organization. The ideal candidate will have strong experience in model governance frameworks, validation processes, AI/ML delivery, and Agile practices and a proven ability to coordinate model documentation, ensure validation readiness, and drive remediation to achieve timely governance and regulatory approvals." That's substantive. Responsibilities: list items: - Own model documentation readiness, gap analysis, and quality reviews. - Coordinate validation preparation, evidence collection, and findings remediation. - Identify gaps in model documentation, testing, and governance artifacts. - Drive remediation of validation findings and documentation deficiencies. - Partner with Model Developers on explainability, monitoring, and performance testing requirements. - Ensure model submissions are audit, regulator, and MRM ready. - Track model lifecycle milestones, approvals, and governance dependencies. - Support ongoing monitoring, implementation validation, and post-production controls. Requirements: maybe the "Required Skills & Qualifications:" list includes both qualifications and skills. We can separate: Requirements (education, years experience) and Skills (technical). Let's parse: Required Skills & Qualifications: - Bachelor's Degree or equivalent experience in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. - 4+ years supporting model development, validation, governance, AI/ML delivery, or risk management programs. - Experience coordinating deliverables across model developers, validators, technology, and governance stakeholders. - Hands-on experience with model lifecycle documentation including MDDs, OMPs, AI Risk Assessments, validation evidence packages, implementation documentation, and monitoring deliverables. - Knowledge of validation principles, data quality assessments, testing methodologies, explainability, bias and fairness reviews, and monitoring controls. - Ability to assess documentation quality, identify evidence gaps, drive remediation, and ensure submission readiness. - Strong communication, facilitation, stakeholder management, and organizational skills. - Experience working in Agile environments with multiple concurrent initiatives and competing priorities. - Advanced presentation and documentation review skills are desirable. - Technical skills: Python, SQL, Tableau. Preferred Skills: - Understanding of digital platforms, conversational AI, and intelligent virtual assistant technologies. - Knowledge of Agile, Lean SDLC, and iterative delivery practices. - Ability to operate in a high-paced environment with clear priorities. We could put "Requirements" for education + years experience + coordinating deliverables etc. But many items are skills. Simpler: have a "Requirements" section for the bullet list (excluding technical skills maybe) and a "Skills" section for technical skills and preferred skills. However instruction: Use headings like Requirements, Qualifications, Skills. Could combine qualifications and requirements. But we need to avoid thin sections. Let's decide: - About the role (paragraph) - Responsibilities (ul) - Requirements (education + years experience + coordinating deliverables + ability to assess documentation quality + strong communication + Agile experience) maybe. - Qualifications (maybe same as requirements? Could combine). But we can have "Qualifications" for the bullet list of required qualifications (education, experience, etc.) and "Skills" for technical and preferred skills. But we need to avoid duplication. Let's extract: Qualifications (education + experience): - Bachelor's Degree or equivalent experience in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field. - 4+ years supporting model development, validation, governance, AI/ML delivery, or risk management programs. - Experience coordinating deliverables across model developers, validators, technology, and governance stakeholders. - Ability to assess documentation quality, identify evidence gaps, drive remediation, and ensure submission readiness. - Strong communication, facilitation, stakeholder management, and organizational skills. - Experience working in Agile environments with multiple concurrent initiatives and competing priorities. - Advanced presentation and documentation review skills are desirable. Skills (technical + preferred): - Technical skills: Python, SQL, Tableau. - Preferred Skills: - Understanding of digital platforms, conversational AI, and intelligent virtual assistant technologies. - Knowledge of Agile, Lean SDLC, and iterative delivery practices. - Ability to operate in a high-paced environment with clear priorities. - Hands-on experience with model lifecycle documentation including MDDs, OMPs, AI Risk Assessments, validation evidence packages, implementation documentation, and monitoring deliverables. - Knowledge of validation principles, data quality assessments, testing methodologies, explainability, bias and fairness reviews, and monitoring controls. We could combine those into Skills section. Pay: $64.52/hr (W2). So we need a Pay section with that. Schedule: Hybrid schedule with a minimum of 3 days onsite per week. Also start date: October or ASAP. Could include schedule only if specific. We have schedule info. So Schedule section: Hybrid schedule with a minimum of 3 days onsite per week. Also maybe mention start date? Not required but could be included as part of schedule? The instruction: include a section ONLY when posting has real, specific content for it. So we can include Schedule with hybrid schedule details. Start date maybe not needed but could be included as part of schedule? Might be considered logistics but not schedule. We'll keep schedule as hybrid schedule. Benefits: from "Why BCforward?" bullet list: - Competitive compensation and benefits. - Opportunities for growth with global clients. - A supportive, inclusive culture that values innovation and people. - Exposure to cutting-edge technologies and projects. We'll put those as ul. We must not include boilerplate like equal opportunity, apply now, etc. We need to output only HTML fragment, no html/body tags, no markdown. Let's construct:

About the role

We are seeking a Model Governance / Model Risk Delivery Lead to join our dynamic team supporting Bank of America's Erica, Chat, and Voice Technology organization. The ideal candidate will have strong experience in model governance frameworks, validation processes, AI/ML delivery, and Agile practices and a proven ability to coordinate model documentation, ensure validation readiness, and drive remediation to achieve timely governance and regulatory approvals.

Responsibilities

• Own model documentation readiness, gap analysis, and quality reviews.
• Coordinate validation preparation, evidence collection, and findings remediation.
• Identify gaps in model documentation, testing, and governance artifacts.
• Drive remediation of validation findings and documentation deficiencies.
• Partner with Model Developers on explainability, monitoring, and performance testing requirements.
• Ensure model submissions are audit, regulator, and MRM ready.
• Track model lifecycle milestones, approvals, and governance dependencies.
• Support ongoing monitoring, implementation validation, and post-production controls.

Qualifications

• Bachelor's Degree or equivalent experience in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 4+ years supporting model development, validation, governance, AI/ML delivery, or risk management programs.
• Experience coordinating deliverables across model developers, validators, technology, and governance stakeholders.
• Ability to assess documentation quality, identify evidence gaps, drive remediation, and ensure submission readiness.
• Strong communication, facilitation, stakeholder management, and organizational skills.
• Experience working in Agile environments with multiple concurrent initiatives and competing priorities.
• Advanced presentation and documentation review skills are desirable.

Skills

• Technical skills: Python, SQL, Tableau.
• Hands-on experience with model lifecycle documentation including MDDs, OMPs, AI Risk Assessments, validation evidence packages, implementation documentation, and monitoring deliverables.
• Knowledge of validation principles, data quality assessments, testing methodologies, explainability, bias and fairness reviews, and monitoring controls.
• Understanding of digital platforms, conversational AI, and intelligent virtual assistant technologies.
• Knowledge of Agile, Lean SDLC, and iterative delivery practices.
• Ability to operate in a high-paced environment with clear priorities.

Benefits

• Competitive compensation and benefits.
• Opportunities for growth with global clients.
• A supportive, inclusive culture that values innovation and people.
• Exposure to cutting-edge technologies and projects.

Pay

$64.52/hr (W2)

Schedule

Hybrid schedule with a minimum of 3 days onsite per week.

Check for any filler like "commensurate with experience" etc. Not present. We removed location, duration, job ID, start date, interview process, sponsorship, etc. Those are minor metadata; we could fold location into a short p but instruction says do NOT put Job ID/requisition numbers as headings — fold minor metadata into a short

or drop it. We could include location and duration in a short p maybe under About the role? But we already have About the role paragraph; we could add a short p after it with location and duration. However we must not repeat job title. The location and duration are minor metadata; we could include them in a short p after About the role. But we already have a schedule section; duration is contract length 15 months (potential contract-to-hire). That's also metadata. Could include in a short p under About the role or separate. The instruction: "do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

or drop it." So we can include location, duration, maybe start date in a short p. However we already have schedule section; we could add a p for "Location: Charlotte, NC. Duration: Contract - 15 months (potential contract-to-hire)." But we need to avoid duplication with schedule. It's okay. But we must preserve ALL substantive information. Location and duration are substantive. So we should include them. Where? Could add a p after About the role: "

Location: Charlotte, NC. Duration: Contract - 15 months (potential contract-to-hire).

" That's minor metadata but we keep. Also start date: "Start: October or ASAP." Could be included as minor metadata.