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Data Scientist
- New York, New York, United States
- New York, New York, United States
Über
Pay Range Target Pay Range: $96,900.00-$118,400.00 annually. Full Pay Range: $75,300.00 - $140,100.00 annually. Compensation determined using factors such as relevant job-related skills, experience, and education or training.
Benefits
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
To join our dynamic team, we require candidates to be residents of WA, CA, VA, NC, OR, ID, AZ, TX, GA, or SC. If you're located in Washington state and within a reasonable driving distance from Tukwila, we are requesting that you come into our HQ on Tuesdays & Wednesdays. For those candidates that live outside the commute distance of TFC and in any of our approved remote work locations, this role will be remote. Remote or onsite, we are committed to ensuring you are fully engaged and included in our collaborative environment.
Impact You'll Make As a Data Scientist at BECU, you'll help shape how we understand and engage with our members by turning complex data into meaningful insights and predictive solutions. You'll build models that identify opportunities to strengthen member relationships, improve onboarding experiences, and support financial wellbeing. Working closely with cross-functional partners across marketing, analytics, and product teams, you'll uncover patterns that help BECU anticipate member needs and drive smarter decisions. Your work will power experimentation, predictive insights, and data-driven strategies that elevate how we serve our members. Through advanced analytics and storytelling, you'll help transform data into impactful member experiences.
What You’ll Do
Build Predictive Models: Develop, validate, and deploy statistical and machine learning models that help identify member behaviors, such as engagement patterns, product adoption opportunities, and potential member dormancy or attrition.
Design Experiments and A/B Tests: Lead methodology design for controlled experiments to evaluate onboarding strategies, engagement programs, and marketing initiatives while ensuring statistical rigor and actionable insights.
Transform Data into Insights: Translate complex analytical findings into clear, compelling narratives using visualizations, dashboards, and presentations that support strategic decision-making.
Collaborate Across Teams: Partner with marketing, product, analytics, and engineering teams to define business problems, gather requirements, and deliver data-driven solutions that improve member experiences.
Develop Advanced Datasets: Build and maintain intermediate to complex datasets-including structured and unstructured data-using tools such as Python, SQL, or Spark to support modeling and analysis.
Explore Data for Strategic Opportunities: Use analytical research and exploratory techniques to uncover trends, opportunities, and emerging insights that support divisional and organizational goals.
Support Data Science Excellence: Participate in peer reviews, knowledge-sharing forums, and data science communities to promote high-quality analytics practices and continuous learning.
Manage Model Lifecycle: Monitor model performance, evaluate results, and optimize models over time to ensure continued accuracy, reliability, and business value.
Adapt and Support Business Needs: Take on additional responsibilities and initiatives that support evolving data science priorities across the organization.
This isn't just about ticking off tasks on a list. It's about making a significant, positive change in BECU's journey, where your contributions are valued, and your growth is continually fostered.
What You’ll Gain
The opportunity to apply advanced analytics and machine learning to real-world member engagement and financial wellbeing challenges.
A chance to work on high-impact predictive models that directly influence onboarding experiences, engagement strategies, and product recommendations.
Hands‑on experience building data science solutions within a modern cloud data ecosystem including Snowflake, Azure, and Python-based tools.
Collaboration with cross‑functional teams including marketing, product, analytics, and engineering to solve meaningful business problems.
An environment that encourages innovation, experimentation, and continuous learning in data science and analytics.
The ability to make a direct impact on how BECU serves and supports its members throughout their financial journey.
Qualifications Minimum Qualifications
Bachelor's degree in Data Science, Computer Science, Statistics, or a related field, or equivalent combination of education and experience.
Minimum 2 years of experience in data science, including at least 1 year applying data science in a business or industry setting with proficiency in programming languages such as Python or R, with the ability to build, test, and deploy analytical models.
Working knowledge of statistical analysis and machine learning techniques, with the ability to apply them to real-world business problems.
Proven communication, presentation, and project management skills, with the ability to translate complex analytical findings into clear insights for diverse stakeholders.
Join the Journey Ready to make an indelible impact? Eager to be part of a collaborative and innovative team where your ideas and contributions don't just fill a role but fuel the growth and success of BECU? This is more than a job - it's a chance to elevate your career, skills, and future, all while contributing to the robust operational landscape of BECU.
Embrace the opportunity to grow with us. Apply now, bring your expertise to the table, and let's achieve excellence together at BECU. Your journey of influence, innovation, and impactful contribution starts now.
EEO Statement: BECU 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.
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Sprachkenntnisse
- English
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