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Job Description
Structured overview of role & requirementsAbout This Role
Analyze large-scale datasets to identify data quality issues, fragmented connections, and incorrect associations in audience data.
Validate and test audience outputs and matching behavior using SQL, Python/R, and statistical methods across real-world scenarios.
Collaborate with Product, Engineering, and Data Science teams to improve audience data quality, matching accuracy, and overall product performance.
Minimum Requirements
Bachelor's degree in Analytics, Data Science, Statistics, Mathematics, Computer Science, or related field.
4+ years of experience in data analytics, data quality, or data validation roles.
Strong proficiency in SQL (complex queries, joins, aggregations) and Python or R for data analysis and statistical evaluation.
Experience with data quality assessment, validation methodologies, and exploratory data analysis.
Ideal Candidate Profile
Experienced in audience analytics, identity resolution, or customer identity data domains, with understanding of entity matching and data crosswalks.
Comfortable working with large-scale, complex client/vendor datasets and implementing benchmarking and regression testing workflows.
Able to translate analytical insights into actionable recommendations and collaborate effectively across technical and business teams.