Model Development & Decision Science Director

Columbia Bank•Lake Oswego, OR

1d•$151,000 - $278,000•Onsite

About The Position

The Model Development & Decision Science Director advances the organization’s quantitative modeling, predictive and prescriptive analytics, model performance monitoring, decision science, and AI/ML capabilities. The role strengthens consistency and transparency in modeling practices and guides responsible use of artificial intelligence and emerging technologies. It partners with business, technology, risk, compliance, privacy, operations, and data management stakeholders to deliver scalable, controlled, production-ready analytics that improve decisioning, operational efficiency, risk management, and business performance. The Director briefs executive management and governance forums on model development, AI/ML initiatives, platform modernization, and delivery risks, and helps shape responsible AI adoption and scalable implementation practices through the enterprise AI Center of Excellence. The position is accountable for predictive models, forecasting methodologies, optimization engines, machine learning models, AI-enabled decisioning, and associated model lifecycle management. It leads a multi-level model development and decision science organization, establishes modeling and MLOps standards, sets portfolio priorities, oversees lifecycle activities in partnership with Model Risk Management, and serves as the senior point of accountability for regulatory, governance, examination, documentation, and executive reporting related to models and AI/ML solutions. Enterprise business intelligence reporting, self-service analytics platforms, semantic models, enterprise KPI reporting, data engineering, and data governance remain the responsibility of the Data Management & Analytics function. The role also follows applicable Bank policies, procedures, and regulations; maintains working knowledge of relevant banking regulations; completes required training; and may coach, mentor, or train others. The position is fully onsite at the posted location in Lake Oswego, Oregon. The stated pay range is $151,000–$278,000, and the role may be eligible for performance-based incentive compensation.

Requirements

Bachelor’s degree required.
Advanced degree in Financial Engineering, Applied Mathematics, Statistics, Economics, Finance, Risk Management, or equivalent work experience.
7–10+ years in statistical modeling or model implementation, preferably in banking or finance; required.
4–7+ years leading quantitative modeling, data science, or analytics teams, including managing managers or senior technical leads in a regulated banking or financial services environment; required.
Expertise in quantitative modeling, credit portfolio modeling, CECL, stress testing, scenario analysis, statistical modeling, machine learning, predictive analytics, and AI/ML solution development in a regulated banking environment.
Ability to set organizational direction, manage a broad portfolio of model development, monitoring, AI/ML, and decision science initiatives, and align priorities with enterprise risk, regulatory, and business objectives.
Strong understanding of model risk management, data governance, regulatory expectations, explainability, auditability, privacy, controls, production monitoring, and responsible AI adoption.
Ability to translate complex business, regulatory, economic, and technical needs into practical, scalable, well-controlled analytical solutions.
Executive-level communication and influencing skills, including explaining complex quantitative, AI/ML, technology, and model risk topics to senior leaders, governance committees, auditors, regulators, and cross-functional stakeholders.
Ability to establish operating standards, documentation expectations, governance routines, and quality controls that promote consistency, transparency, accountability, and effective model lifecycle management.
Leadership in organizational design, workforce planning, talent development, succession planning, performance management, and retention of specialized quantitative and data science talent.
Strategic thinking and demonstrated ability to lead change, foster innovation, adopt emerging modeling and technology tools, and partner across Business, Risk, Technology, Compliance, Privacy, and Data Management functions.
Technical fluency with Python, SQL, distributed data processing, cloud-based analytics platforms, and MLOps practices.
Experience with tools such as Databricks, Snowflake, Spark, MLflow, scikit-learn, XGBoost, or similar technologies.
Experience advancing scalable model deployment, CI/CD automation, experiment tracking, performance monitoring, production governance, and technology controls in partnership with platform and engineering teams.

Nice To Haves

Doctoral degree preferred.
3+ years of experience with Commercial Real Estate Risk Modeling preferred.

Responsibilities

Lead development, implementation, performance monitoring, and enhancement of quantitative models, predictive and prescriptive analytics, AI/ML methodologies, forecasting approaches, optimization models, and decision science solutions across credit risk, fraud, finance, treasury, compliance, and other enterprise use cases.
Define modeling standards, performance-monitoring expectations, model documentation requirements, MLOps practices, best practices, and enabling technologies.
Lead a multi-level model development and decision science organization, including talent development, succession planning, delivery quality, and team performance.
Set portfolio priorities for model development, monitoring, AI/ML, and decision science initiatives, balancing business value, regulatory expectations, resource capacity, execution risk, and production readiness.
Partner with Model Risk Management on the full model lifecycle, including validation, monitoring, recalibration, redevelopment, remediation, and compliance with governance standards.
Partner with senior business, risk, compliance, privacy, technology, and data management leaders to identify, prioritize, resource, and deliver high-impact analytics, modeling, decision science, and AI solutions aligned with enterprise goals.
Serve as the senior point of accountability for regulatory, governance, examination, documentation, and executive reporting related to models and AI/ML solutions.
Lead AI innovation and automation delivery for the enterprise AI Center of Excellence, including controlled, explainable, auditable AI/ML and automation solutions and ownership of business-facing AI/ML use cases, predictive models, and automated decisioning solutions.
Define model-development technology requirements, model deployment standards, experiment management practices, performance-monitoring expectations, and MLOps standards.
Comply with applicable bank regulations and policies, keep current on regulation changes, and complete required annual or job-specific training.
Maintain working knowledge of applicable Bank policies and procedures concerning Bank Secrecy Act, Regulation CC, Regulation E, Bank Security, and other relevant regulations.
Coach, mentor, or train others and teach coursework as a subject matter expert when asked.
Demonstrate and foster Columbia’s corporate culture, take personal initiative, serve as a positive example, and embrace the vision to become “Business Bank of Choice.”
Perform other duties as assigned.

Benefits

Medical, dental, and vision plans
401(k) retirement savings plan with employer match for qualifying associate contributions
Employee assistance program
Life insurance
Disability insurance
Tuition assistance
Mental health resources
Identity theft protection
Legal support
Auto and home insurance
Pet insurance
Access to an online discount marketplace
Paid vacation
Paid sick days
Paid volunteer days
Paid holidays
Performance-based incentive compensation may be available