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.

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

Preferred

• 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)

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