Quantitative Financial Analyst

Overview

This position is for a Quantitative Financial Analyst supporting smarter Treasury and balance sheet decisions. The role applies quantitative thinking, financial modeling, and coding to fixed income, interest rate risk, and analytics across Asset Liability Management (ALM), mortgage and balance sheet hedging, pricing, profitability, and portfolio risk.

The target pay range for this position is $106,600.00–$130,100.00 annually. The full pay range is $82,900.00–$154,000.00 annually. Compensation decisions are determined based on factors such as relevant job-related skills, experience, and education or training. If an offer is made, individual qualifications will be considered. In addition to salary, performance-based compensation incentives may be available; targets vary by role.

Responsibilities

• Turn quantitative analysis into decisions by applying financial modeling to help Treasury and business leaders understand interest rate risk, profitability, portfolio behavior, and balance sheet opportunities.
• Advance ALM & risk analytics including analysis across NII and Economic Value/EVE sensitivity, duration and convexity, scenario and stress testing, deposit behavior, loan prepayments, and other balance sheet risk measures.
• Enhance and maintain financial models by understanding existing Treasury models, challenging assumptions, recommending improvements, maintaining model parameters, and extending analytical capabilities as business needs evolve.
• Build new solutions by developing quantitative models and analytical applications for new questions and translating ambiguous business problems into structured analytical solutions.
• Modernize pricing analytics by supporting the transition of pricing models to Snowflake and helping build attribution and sensitivity analytics supporting offset center P&L and profitability insights.
• Support portfolio & hedging decisions using fixed income valuation, derivatives, duration, convexity, and risk-management concepts for mortgage portfolio and broader balance sheet hedging activities.
• Automate & scale analytics using Python and Excel/VBA to automate processes, improve analytical workflows, and create more efficient and scalable solutions.
• Partner across the business with Treasury, Enterprise Risk Management, Credit Risk, Product, and portfolio leaders to explain models, support validation, and help establish meaningful guardrails and guidelines.
• Strengthen model governance by maintaining model documentation, assumptions, and parameters while navigating model governance and validation processes.

Qualifications

Minimum Qualifications

• Master’s degree or PhD in Financial Engineering, Quantitative Finance, Mathematics, Statistics, Econometrics, Physics, or a closely related quantitative field.
• Quantitative and financial modeling expertise, including demonstrated experience developing, applying, or enhancing financial or statistical models; strong knowledge of fixed income, interest rate risk, valuation, duration, convexity, derivatives, and portfolio risk management; and advanced proficiency in Python and Excel/VBA.
• Demonstrated ability to independently solve complex and ambiguous problems, challenge assumptions, improve analytical approaches, and translate quantitative findings into clear insights for diverse audiences, with curiosity and learning agility to quickly build knowledge across Treasury and financial concepts.

Preferred Qualifications

• Applied experience with Asset Liability Management (ALM), Treasury analytics, FTP, capital management, balance sheet strategy, or profitability analytics.
• Experience with NII/EVE sensitivity analysis, deposit behavioral modeling, loan prepayment modeling, scenario analysis, or stress testing.
• Experience with mortgage hedging, fixed income portfolio management, derivatives analytics, rates/trading support, investment analytics, or other interest-rate hedging environments.
• Experience building quantitative models from scratch through professional experience, internships, or graduate-level projects.
• Experience with Snowflake and Git/GitHub, or similar modern data and development environments.
• Experience using AI-assisted development or AI pair-programming tools as part of an analytical or coding workflow.
• Experience within a bank, credit union, mortgage company, financial services organization, or consulting environment is helpful but not required.

Compensation & Benefits

• Target pay range: $106,600.00–$130,100.00 annually
• Full pay range: $82,900.00–$154,000.00 annually
• 401(k) Company Match (up to 3%)
• 4% annual contribution to your 401(k) by the employer
• Medical, Dental, and Vision (family contributions as well)
• PTO Program + Exchange Program
• Tuition Reimbursement Program
• Volunteer time off and donation match
• Performance-based compensation incentives may be available (targets vary by role)

Location & Work Setup

Candidates must be residents of WA, OR, ID, AZ, TX, GA, NC, VA, CA, or SC.

• If located in Washington state and within a reasonable driving distance from Tukwila, the expectation is to come into the HQ Tuesdays & Wednesdays.
• For candidates outside the commute distance of TFC and in any approved remote work locations, this role will be remote.

Remote or onsite, the organization is committed to ensuring employees are fully engaged and included in a collaborative environment.

Equal Opportunity

The employer is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, veteran status, disability, sexual orientation, gender identity, or any other protected status.