BECU is a financial institution focused on serving its members and communities. The Senior Data Scientist in Marketing Analytics will partner with Marketing to translate business challenges into data-driven solutions, utilizing statistical and machine learning models to optimize performance and drive measurable results.
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
- 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)