Remote ALM Quantitative Finance Analyst

BECU; Arizona; On-site; USD 83,000 - 154,000; Full time

Benefits offered by this job

401(k) Company Match (up to 3%)

4% annual 401(k) contribution

Medical, Dental and Vision

PTO + Exchange Program

Tuition Reimbursement

Volunteer time off

Job summary

BECU is seeking a Quantitative Financial Analyst to join our Treasury and ALM teams. You will apply quantitative methods, financial modeling, and coding to support interest rate risk decisions, pricing analytics, and balance sheet optimization for our member-focused financial institution.

You should have a strong foundation in fixed income, Python and Excel/VBA, and the ability to translate complex models into actionable insights for Treasury, Risk, and Portfolio leaders.

Qualifications

• Master’s degree or PhD in Financial Engineering, Quantitative Finance, Mathematics, Statistics, Econometrics, Physics, or closely related field.

Responsibilities

• Apply financial modeling and quantitative analysis to understand interest rate risk and profitability for the Treasury and ALM decisions.
• Support NII/EVE sensitivity, duration, convexity, scenario and stress testing, and balance sheet risk measures.
• Maintain and improve existing Treasury models, parameters, and governance processes.
• Develop quantitative models and analytical applications to address new business questions.
• Move pricing analytics toward Snowflake and build attribution and sensitivity analytics.
• Collaborate with Treasury, Risk, Credit, Product, and portfolio teams to explain models and recommendations.

Skills

Financial modeling

Quantitative analysis

Independent problem solving

Communication of insights

Education

Master's or PhD

Tools

Python

Excel/VBA

Job description

BECU is seeking a Quantitative Financial Analyst to join our Treasury and ALM teams. You will apply quantitative methods, financial modeling, and coding to support interest rate risk decisions, pricing analytics, and balance sheet optimization for our member-focused financial institution.

You should have a strong foundation in fixed income, Python and Excel/VBA, and the ability to translate complex models into actionable insights for Treasury, Risk, and Portfolio leaders.