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.

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningstatistical modelingdata analysisfeature engineeringA/B testingMLOpsPythonRSQLdata preparation

Soft Skills

communicationpresentationproject managementcollaborationmentoringstorytellinganalytical thinkingproblem-solvingleadershipguidance

Certifications

Bachelor's degree in Data ScienceBachelor's degree in Computer ScienceBachelor's degree in Statistics