Quantitative Modeler & Data Scientist

Columbia Banking System; Lake Oswego (OR); On-site; USD 100,000 - 150,000; Full time

Benefits offered by this job

Healthcare coverage

401(k) retirement plan

Employee assistance program

Life insurance & disability

Tuition assistance

Identity theft protection

Discount marketplace

Paid vacation & holidays

Incentive compensation

Job summary

Columbia Banking System seeks a quantitative modeler and data scientist to design, implement, and maintain modeling solutions that support business decisions, risk management, and strategic initiatives.

This onsite role in Lake Oswego, OR offers a salary range of USD 100,000 - 150,000 per year. Requires at least 2 years of experience and a Master’s Degree in a quantitative field.

Qualifications

• Master’s Degree in economics, mathematics, statistics, financial engineering, quantitative finance, or actuarial science.
• 2-4 years in banking or financial services as a Data Scientist or related role.
• Knowledge of SR 26-2, Basel II/III, and DFAST.
• Proficiency with Python, PySpark, R, Matlab, Excel VBA, and SQL.
• Ability to translate complex analysis into actionable business insight.

Responsibilities

• Design, estimate, implement, test, document, monitor, and maintain models for business decisions and risk management.
• Develop and support models for default, loss severity, fraud detection, customer analytics, and credit risk.
• Contribute to governance, documentation, and model risk management practices.
• Perform quantitative analysis and data mining using Python, SQL, R, and Spark technologies.
• Collaborate with stakeholders to align analytical approaches with regulatory expectations.

Skills

Statistical modeling

Econometric forecasting

Machine learning

Quantitative analysis

Education

Master’s Degree in a quantitative field

Tools

Python

PySpark

R

Matlab

SQL

Databricks

Snowflake

Azure

AWS

Job description

Columbia Banking System is seeking a quantitative modeler and data scientist to design, implement, and maintain modeling solutions that support business decisions, risk management, and strategic initiatives. The role spans statistical, mathematical, economic, financial, and AI/ML-driven approaches, with active involvement in model validation, governance, documentation, and performance monitoring in alignment with regulatory expectations, including SR 26-2.

This onsite position is located in Lake Oswego, OR, with a salary range of USD 100,000 - 150,000 per year. The role requires at least 2 years of relevant experience and a Master’s Degree in a quantitative or economics-focused field.

What you will do

• Design, estimate, implement, test, document, monitor, and maintain statistical, financial, economic, machine learning, and AI-enabled models used for business decision-making, risk management, forecasting, and strategic initiatives.
• Develop and support models for default, loss severity, fraud detection, customer analytics, financial planning, credit risk, anti-money laundering, and asset liability management, along with other financial and non-financial applications.
• Support responsible adoption of AI/ML capabilities by contributing to governance, documentation, monitoring, control design, and appropriate use standards for emerging analytics technologies.
• Conduct quantitative analysis, modeling, data mining, and programming using tools such as Databricks, Snowflake, SQL, R, Python, and other approved analytics platforms to produce insights, test hypotheses, and recommend actions.
• Partner with business, technology, risk, compliance, and governance stakeholders to define analytical approaches and modeling solutions aligned with internal standards and applicable regulatory expectations, including SR 26-2.
• Research and develop quantitative tools and techniques to measure and analyze model risk, documenting strengths and limitations.
• Assess model conceptual foundations, including model specification, assumptions, limitations, variable selection, underlying data, developmental evidence, and documentation.
• Interview model developers/vendors and model owners to understand business context and facilitate adoption of model risk management standards.
• Stay current on banking regulations affecting model risk management across the organization.
• Advocate sound quantitative model development, model monitoring, and AI governance practices.
• Propose and execute model validation tests for new and existing models in the inventory.
• Support production of regular and ad-hoc reports on individual and bank-level model findings for Senior Management and regulators.
• Coordinate with the model validation team on changes to the bank’s model inventory or end user applications.
• Perform required compliance activities for assigned job functions, follow bank policies and procedures, and complete annual or job-specific training.
• Maintain working knowledge of written policies and procedures related to the Bank Secrecy Act, Regulation CC, Regulation E, Bank Security, and other applicable regulations.
• May coach, mentor, or train others and teach coursework as a subject matter expert.
• Embrace and help foster Columbia’s corporate culture through actions and words; take personal initiative and serve as a positive example.
• Support Columbia’s vision to become the “Business Bank of Choice”.
• May perform other duties as assigned.

Required qualifications

• Master’s Degree in economics, mathematics, statistics, financial engineering, quantitative finance, or actuarial science.
• 2-4 years in banking or financial services as a Data Scientist, Statistician, Quantitative Risk Analyst, Model Developer, Model Validator, or similar.
• Knowledge of regulatory requirements related to model risk management, including FRB/OCC SR 26-2, Basel II/III capital requirements, and Dodd-Frank Act Stress Testing (DFAST).
• Advanced understanding of statistical modeling, econometric forecasting, machine learning, data extraction and processing, with proven ability to apply these methods.
• Experience with analytics software including Python, PySpark, R, Matlab, Excel VBA, and SQL, plus relational databases and/or cloud platforms such as Azure, AWS, Databricks, and Snowflake.
• Communication skills to translate complex statistical or economic analysis into practical implications for business teams and Senior Management.
• Strong organizational skills to manage multiple concurrent projects and meet strict deadlines.
• Ability to proactively learn emerging statistical, econometric, and mathematical modeling techniques and understand their implications in a banking environment.
• Critical thinking, business intuition, intellectual curiosity, and execution capability.
• Certification as FRM, CFA, or CQF, or progress toward one of these certifications.

Tools and technologies

• Databricks, Snowflake, SQL, R, Python, PySpark, Matlab, Excel VBA
• Azure, AWS

Benefits

• Comprehensive healthcare coverage including medical, dental, and vision
• 401(k) retirement savings plan with employer match for qualifying associate contributions
• Employee assistance program
• Life insurance and disability insurance
• Tuition assistance, mental health resources, and identity theft protection
• Legal support, auto and home insurance, and pet insurance
• Access to an online discount marketplace
• Paid vacation, sick days, volunteer days, and holidays

Additional compensation: The role may be eligible for performance-based incentive compensation, with details provided during the recruitment process.

Equal opportunity: Columbia Bank is an equal opportunity and affirmative action employer committed to employing, engaging, and developing a diverse workforce. Columbia Bank does not accept unsolicited resumes or applications from staffing and recruiting agencies.