Senior Data Scientist

Role Overview

• Build Advanced Machine Learning Models: Design, develop, test, and deploy advanced statistical and machine learning models that solve complex business problems and deliver measurable business value.
• Explore and Prepare Data for Modeling: Conduct exploratory data analysis, feature engineering, and dataset preparation to support robust model development and experimentation.
• Evaluate and Improve Model Performance: Monitor and refine models to ensure accuracy, scalability, and sustained business impact while identifying opportunities for optimization.
• Design and Execute Experiments: Lead hypothesis-driven experimentation, including A/B testing and controlled experiments, to inform product, marketing, and business decisions.
• Contribute to MLOps and Model Deployment: Support the development and implementation of scalable MLOps frameworks to enable reliable model deployment, monitoring, and lifecycle management.
• Translate Business Needs into Data Solutions: Partner with business stakeholders to understand objectives and convert complex challenges into actionable analytical strategies.
• Communicate Insights Clearly: Present findings and recommendations through compelling storytelling, visualizations, and presentations tailored to both technical and non-technical audiences.
• Collaborate Across Teams: Work closely with data engineers, analysts, product teams, and business leaders to integrate data science solutions into production systems and decision workflows.
• Mentor and Guide Team Members: Provide guidance to fellow data scientists and analysts on technical approaches, modeling strategies, and career development.
• Advance Data Science Best Practices: Contribute to the evolution of data science standards, processes, and best practices across the organization.

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 a related analytical discipline, with demonstrated success developing predictive models and delivering data-driven solutions that influence business decisions with proficiency in programming languages such as Python, R, and SQL, including experience building scalable analytical models and working with large datasets.
• Working knowledge of statistical modeling, machine learning techniques, and core data engineering principles, with the ability to apply them to complex real-world problems.
• Proven communication, presentation, and project management skills, with the ability to translate complex analytical findings into clear, actionable insights for technical and non-technical stakeholders.

Tech Stack

• Python
• SQL

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