Sr Data Scientist - Member & Prescreen Modeling

About BECU

BECU is a financial institution of 1.5 million members and over $30 billion in managed assets that focuses on people, not profits.

The Target Pay Range for this position is $–$ annually. The full Pay Range is $91,000.00–$ annually. Compensation decisions are determined using factors such as relevant job‑related skills, experience, and education or training. In addition to your salary, performance‑based incentives are available.

• 401(k) Company Match (up to 3%)
• 4% annual contribution to your 401(k) by BECU
• Medical, Dental and Vision (family contributions as well)
• PTO Program + Exchange Program
• Tuition Reimbursement Program
• BECU Cares volunteer time off + donation match

Candidates must be residents of WA, CA, VA, NC, OR, , AZ, TX, GA, or SC. Residents within a reasonable driving distance from Tukwila will be requested to work onsite Tuesdays and Wednesdays. Remote work is possible for candidates outside the commute zone.

As a Senior Data Scientist at BECU, you will help shape how data drives member growth, marketing strategy, and enterprise decision‑making. You will partner closely with Marketing, Product, and Technology teams to solve complex business challenges through predictive analytics, machine learning, and experimentation.

Through advanced modeling, targeting optimization, and translating insights into action, you will improve member acquisition, cross‑sell opportunities, and campaign performance, strengthening personalized experiences and member relationships. Your storytelling and data science expertise will directly contribute to BECU's commitment to improving the financial well‑being of our members.

• Partner with Marketing to solve business challenges by translating objectives into analytical strategies that improve targeting, eligibility, and campaign performance.
• Build predictive models that support prescreen targeting, prospect prioritization, propensity modeling, segmentation, eligibility decisioning, and uplift modeling.
• Optimize campaign performance through A/B testing, champion‑challenger testing, and experimentation to evaluate effectiveness and identify performance drivers.
• Transform data into business insights, communicating actionable recommendations and quantifying impact via metrics such as conversion lift, engagement improvement, and ROI.
• Operationalize data science solutions by partnering with Data Engineering and Technology teams to deploy scalable models, support production‑ready analytics, and maintain reliable pipelines.
• Influence through data storytelling by presenting findings and recommendations with compelling visualizations and executive‑ready presentations.
• Collaborate across the enterprise with data engineers, analysts, product managers, marketers, and leaders to integrate predictive analytics into decision‑making and workflows.
• Mentor and develop others by providing guidance, coaching, and technical mentorship while promoting best practices.
• Advance data science practices by contributing to evolving standards, modeling approaches, experimentation frameworks, and MLOps capabilities.
• Take on additional responsibilities as assigned to support the evolving needs of the team and organization.

• The opportunity to solve complex business challenges that directly influence member acquisition, engagement, and growth.
• Visibility and collaboration with leaders across Marketing, Product, Technology, Analytics, and Data Engineering.
• A role where your expertise in predictive modeling, experimentation, and machine learning directly shapes enterprise strategy and performance.
• Opportunities to mentor peers while advancing BECU’s data science capabilities.
• A culture that values innovation, continuous learning, collaboration, and measurable impact.

Minimum Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related quantitative discipline, or equivalent work or educational experience.
• Minimum 5 years of experience developing predictive analytics and machine learning solutions, with success in designing statistical models, applying advanced techniques, and…