Quantitative Finance Analyst: ALM & Risk Modeling

BECU; Virginia (MN); Hybrid; USD 107,000 - 130,000; Full time

Benefits offered by this job

401(k) Match

Annual 4% 401(k) contribution

Medical, Dental and Vision

PTO + Exchange Program

Tuition Reimbursement

Volunteer time off + donation match

Job summary

BECU is seeking a highly quantitative Financial Analyst to join Treasury analytics. You will apply financial modeling, fixed income, and risk-management concepts to support balance sheet decisions and pricing analytics. You’ll work with Python and Excel/VBA to automate workflows and scale solutions.

The role offers opportunities to advance ALM analytics, collaborate across Risk, Product, and Treasury teams, and contribute to modern data environments like Snowflake and AI-assisted development.

Qualifications

• Master’s or PhD in a quantitative field with finance focus.
• Strong knowledge of fixed income, interest rate risk, valuation, duration, convexity, derivatives, and portfolio risk management.
• Proven ability to translate quantitative findings into clear business insights.

Responsibilities

• Turn quantitative analysis into actionable decisions for Treasury and leadership.
• Support analysis across NII, EVE sensitivity, duration, convexity, stress testing, and balance sheet measures.
• Improve and extend Treasury models; maintain parameters and governance.

Skills

Quantitative analysis

Financial modeling

Python

Excel/VBA

Fixed income

Interest rate risk

Derivatives

Portfolio risk

Model governance

Education

Master’s degree in Financial Engineering or related field

PhD in quantitative field (optional)

Tools

Snowflake

Git/GitHub

Job description

BECU is seeking a highly quantitative Financial Analyst to join Treasury analytics. You will apply financial modeling, fixed income, and risk-management concepts to support balance sheet decisions and pricing analytics. You’ll work with Python and Excel/VBA to automate workflows and scale solutions.

The role offers opportunities to advance ALM analytics, collaborate across Risk, Product, and Treasury teams, and contribute to modern data environments like Snowflake and AI-assisted development.