Sr Business Data Scientist, Marketing Analytics

BECU•St. David's, WA

1d•$91,000 - $169,400•Hybrid

About The Position

As a Senior Data Scientist, Marketing Analytics at BECU, you’ll serve as a strategic partner to Marketing—helping translate business challenges into data-driven solutions that influence decisions, optimize performance, and drive measurable results. This role is deeply business-facing. You’ll work side-by-side with stakeholders to define problems, design analytical approaches, and guide decisions through data. While you’ll leverage statistical and machine learning models, success in this role is defined by your ability to connect those solutions to real business outcomes and adoption.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, or a related quantitative field, or an equivalent combination of education and professional experience.
Minimum 5 years of experience in data science or analytics, with a strong focus on business-facing problem solving and proven experience partnering with business teams (preferably Marketing) to translate needs into analytical solutions
Experience building and applying statistical, machine learning models in real-world business contexts, and designing and analyzing experiments (A/B testing, campaign optimization, or similar frameworks)
Strong communication skills with the ability to present insights and influence decisions across non-technical stakeholders
Proficiency in Python, R, and SQL

Nice To Haves

Advanced degree (Master’s or PhD) in a quantitative discipline preferred.
Experience working within financial services or regulated industries.
Experience with cloud platforms such as AWS, Azure, or GCP.
Experience with MLOps tools such as MLflow, Airflow, Kubeflow, or similar frameworks.
Familiarity with BI tools such as Tableau or Power BI and marketing analytics platforms such as Salesforce Marketing Cloud or Google Analytics.
Experience designing systems for large-scale data processing (e.g., Snowflake, BigQuery, Redshift, Spark).

Responsibilities

Partner with Marketing to Define and Solve Problems – Work closely with marketing stakeholders to understand business challenges, define success metrics, and translate needs into analytical approaches that drive performance across campaigns and channels.
Design and Deliver Data-Driven Solutions – Apply statistical analysis and machine learning to develop solutions that address business needs, then present findings, influence decisions, and gain alignment on adoption.
Lead Experimentation and Optimization – Develop and manage testing frameworks (A/B testing, campaign experimentation) across channels and markets. Analyze results and provide clear recommendations to improve performance and inform future strategy.
Translate Results into Business Impact – Clearly communicate insights and quantify outcomes (e.g., campaign performance lift, engagement improvements, ROI) to ensure stakeholders understand the value and take action.
Partner to Operationalize Solutions – Collaborate with Technology and Engineering teams to transition validated models into production, supporting implementation through scalable pipelines and processes.
Influence Through Storytelling – Present insights and recommendations to both technical and non-technical audiences, including senior stakeholders, to drive alignment and decision-making.