Model Development & Decision Science Director

Columbia Bank; Lake Oswego (OR); On-site; USD 151,000 - 278,000; Full time

Benefits offered by this job

Healthcare coverage

401(k) plan with employer match

Tuition assistance

Life insurance

Disability insurance

Paid vacation

Job summary

Columbia Bank is seeking a senior leader to advance quantitative modeling, AI/ML, and decision science across credit risk, fraud, finance, and treasury. You will build scalable, well-governed analytics platforms and ensure production readiness with robust monitoring and risk controls.

The role requires 7–10+ years in statistical modeling, 4–7+ years leading teams, and strong collaboration with Risk, Compliance, and Technology. On-site Lake Oswego, OR.

Qualifications

• 7-10+ years in statistical modeling or model implementation.
• 4-7+ years leading quantitative modeling, data science, or analytics teams in regulated banking or financial services.
• 3+ years experience with Commercial Real Estate Risk Modeling.
• Strong understanding of model risk management, data governance, and governance controls.

Responsibilities

• Lead development, monitoring, and enhancement of quantitative models, AI/ML, and decision science across enterprise use cases.
• Define model development standards, performance monitoring, and MLOps practices.
• Partner with risk, compliance, data management, and technology stakeholders to deliver production-ready analytics solutions.
• Brief executive management and governance forums on model initiatives and delivery risks.

Skills

Python

SQL

MLOps

Databricks

Snowflake

Education

Bachelor's Degree in Financial Engineering or related field

Advanced degree in Financial Engineering, Applied Mathematics, Statistics, Economics, Finance

Tools

MLflow

scikit-learn

XGBoost

Spark

Job description

About the Role:

Responsible for advancing the organization’s quantitative modeling, predictive and prescriptive analytics, model performance monitoring, decision science and AI/ML capabilities. Responsible for strengthening consistency and transparency in modeling practices and guide the responsible use of artificial intelligence and other emerging technologies in model development and decision science. Partners closely with business, technology, risk, compliance, and operations stakeholders to deliver scalable, well-controlled, and production-ready analytics solutions that improve decisioning, operational efficiency, risk management, and business performance. Regularly briefs executive management and risk/governance forums on model development, AI/ML initiatives, platform modernization, and delivery risks, and serves as a critical leader within the enterprise AI Center of Excellence by helping shape responsible AI adoption, governance, and scalable implementation practices. Accountable for predictive models, forecasting methodologies, optimization engines, machine learning models, AI-enabled decisioning and associated model lifecycle management. Lead the development, implementation, performance monitoring and ongoing 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 to strengthen analytical quality, transparency, and forecasting capabilities Lead a multi-level model development and decision science organization, with responsibility for 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 to oversee 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 predictive analytics, quantitative 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 in support of the enterprise AI Center of Excellence agenda, including development and deployment of controlled, explainable, auditable AI/ML and automation solutions that improve decisioning, efficiency, risk management, and business performance. This includes 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 for quantitative, forecasting, 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. Demonstrates compliance with all bank regulations for assigned job function and applies to designated job responsibilities– knowledge may be gained through coursework and on-the-job training. Keeps up to date on regulation changes. Follows all Bank policies and procedures, compliance regulations, and completes all required annual or job-specific training. Maintain a working knowledge of Bank's written policies and procedures regarding Bank Secrecy Act, Regulation CC, Regulation E, Bank Security and other regulations as applicable to this job description. May be asked to coach, mentor, or train others and teach coursework as subject matter expert. Actively learns, demonstrates, and fosters the Columbia corporate culture in all actions and words. Takes personal initiative and is a positive example for others to emulate. Embraces our vision to become “Business Bank of Choice” May perform other duties as assigned.

About You:

Bachelor’s Degree. Required. Advance Degree in Financial Engineering, Applied Mathematics, Statistics, Economics, Finance, Risk Management or equivalent work experience. Doctoral degree preferred. 7-10+ years in statistical modeling or model implementation, preferably in the banking or finance industry. Required 4-7+ years Experience leading quantitative modeling, data science, or analytics teams, including experience managing managers or senior technical leads in a regulated banking or financial services Required 3+ years Experience with Commercial Real Estate Risk Modeling Preferred 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. Demonstrated capability to set organizational direction, manage a broad portfolio of model development, monitoring, AI/ML, and decision science initiatives, and align delivery 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 that improve decisioning, risk management, operational efficiency, and business performance. Executive-level communication and influencing skills, including the ability to explain complex quantitative, AI/ML, technology, and model risk topics to senior leaders, governance committees, auditors, regulators, and cross-functional stakeholders. Proven ability to establish operating standards, documentation expectations, governance routines, and quality controls that promote consistency, transparency, accountability, and effective model lifecycle management across teams. Strong leadership in organizational design, workforce planning, talent development, succession planning, performance management, and retention of specialized quantitative and data science talent. Strategic thinker with demonstrated ability to lead change, foster innovation, adopt emerging modeling and technology tools, and partner effectively across Business, Risk, Technology, Compliance, Privacy, and Data Management functions. Technical fluency with Python, SQL, distributed data processing, cloud-based analytics platforms, MLOps practices, and 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.

The pay range for this role is $151,000.00 - $278,000.00 The pay rate for the selected candidate is dependent upon a variety of non-discriminatory factors including, but not limited to, job-related knowledge, skills, and experience, education, and geographic location. The role may be eligible for performance-based incentive compensation, and those details will be provided during the recruitment process.

Primary Location:

Ability to work fully onsite at posted location(s). 5885 Meadows Road Suite 300 Lake Oswego OR 97035

Our Benefits:

• eligible associates comprehensive healthcare coverage (medical, dental, and vision plans)
• a 401(k)-retirement savings plan with employer match for qualifying associate contributions
• an 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
• sick days
• volunteer days
• holidays

Our Commitment to Diversity:

Columbia Bank is an equal opportunity and affirmative action employer committed to employing, engaging, and developing a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sex, age, sexual orientation, gender identity, gender expression, protected veteran status, disability, or any other applicable protected status or characteristics.

If you require an accommodation to complete the application or interview(s), please let us know by email: [e-mail].

At Columbia Bank, we’re redefining what it means to bank and to build a career. As the West’s premier banking experience, we combine the strength and scale of a leading financial institution with the heart and mindset of a community bank. With more than 350 locations across eight states, we deliver relationship-based service backed by regional expertise and resources that help families and businesses thrive. Our culture is built on Do RIGHT, which means: Relationships: We create authentic connections with customers, colleagues, and communities. Impact: Every role here makes a meaningful difference in people’s lives and local economies. Growth: We invest in your success with career development, mentorship, and learning opportunities. Heart: We care deeply about doing what’s best for our customers and each other. Trust: Integrity and transparency guide everything we do.

Why work for Columbia Bank? A strong, stable financial foundation with over $67 billion in assets and a diverse portfolio that supports flexibility and opportunity. A culture of belonging and purpose, where your ideas matter and your work has impact. Competitive benefits and flexibility designed to help you thrive personally and professionally. Community engagement that matters, from supporting local businesses to empowering youth through financial literacy initiatives.