Job Duties: Design, run and analyze the results of A/B tests of new recommendation algorithms and strategies; develop new testing and test analysis methodologies. KPI reporting and monitoring including anomaly detection tools and advanced measurement approaches. Conduct exploratory data analysis (e.g. clustering/segmentation) to generate new insights & inform our product recommendation roadmap and develop in-house automated tools. Design and run A/B tests of our latest recommendations algorithms. Monitor recommendation models to identify potential issues, determine root cause. Build productive relationships with our product, engineering and machine learning stakeholders and communicate key insights and recommendations to cross functional executive leaders across the organization. Position is based in Seattle, WA office; however, telecommuting may be allowed. 

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Minimum Requirements: Requires a Masters degree (or foreign equivalent) in Engineering, Computer Science, Information Systems, Mathematics, Statistics, Analytics, Operations Research, or a directly related field plus two (2) years of experience in an analytical role. In the alternative, will accept a Bachelors degree (or foreign equivalent) in Engineering, Computer Science, Information Systems, Mathematics, Statistics, Analytics, Operations Research, or a directly related field plus five (5) years of progressive, post-bachelors experience in an analytical role.

Special Skill Requirements: Experience must include two (2) years of experience in at least five (5) of the following (experience may be gained concurrently):
1.Analytics or Data Science experiences with e-commerce companies;
2.Coding in SQL including use of aggregate functions, query optimization, stored procedures, or string parsing;
3.DBT/Vertica/Presto or similar;
4.Quantitative analyses on large data sets and synthesizing findings using SQL, Python, or Python tools, including Jupyter notebooks, functions, pandas, sklearn, or matplotlib;
5.Validating user hypotheses using A/B testing;
6.Machine learning algorithms/techniques (including decision trees, random forest, or deep learning) within a business context;
7.Version control using GIT;
8.Dimensional Data Modeling, Star Schemas, or Looker;
9.GCP database development including designing queries, stored procedures, or performance tuning for BigQuery;
10.Developing presentations using Visio, Google Slides, or PowerPoint;
11.Performing data ETL.
Telecommuting may be allowed.

Senior Technical Analyst (Multiple Positions)

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