Position Title:

Product Quality Data Analyst Location:

Hybrid - Bothell Washington 98021

Duration:

12 months Hours per

Week:

40 (8 hrs/day)

Product Quality Data Analyst Job Responsibilities:

Handles analysis of complex datasets using advanced statistical methods and machine learning techniques to uncover deep insights that inform strategic business decisions and operational efficiencies. Creates sophisticated predictive models and data visualizations, utilizing tools like Python, R, and Palantir, to forecast trends, patterns, and anomalies for proactive decision-making, working under limited supervision. Develops, documents, and disseminates comprehensive methodologies, processes, and analytical findings, ensuring transparency, reproducibility, and facilitating cross-functional knowledge sharing and collaboration. Presents complex data-driven insights and strategic recommendations to senior stakeholders, effectively translating intricate analytical results into clear, actionable business strategies and influencing key decision-making processes. Monitors, maintains, and continuously improves the performance of deployed models, conducting regular reviews, updates, and optimizations to ensure sustained accuracy, relevance, and business impact. Interacts and collaborates with cross-functional teams, including IT, data engineering, and various business units, to ensure the successful operationalization, integration, and scaling of data science solutions across the organization.

Requirements:

Minimum required

Education:

Bachelor's or Master's Degree in Information Management, Information Systems, Computer Science, Data Analytics, or equivalent. Minimum required

Experience:

Minimum 5+ years of experience with a Bachelor's degree in areas such as Data Analytics, Data Modeling, or equivalent OR no prior experience required with a Master's Degree.

Preferred Skills:

Data Analysis & Interpretation Data Harmonization & Processing Data Modeling Data Quality Assurance Statistical Methods Statistical Programming Software Business Intelligence Tools Data Mining Machine Learning Engineering Fundamentals Research & Analysis Structured Query Language (SQL) Regulatory Compliance