Product Analytics Data Analyst
Job Responsibilities:
ā¢ Partner with teams within Product Operations, the broader Global Operations organization, Data Science, Data Engineering, Product and Engineering teams to solve problems and identify trends and opportunities
ā¢ Independently analyze data, conduct research, and synthesize feedback into plans, processes, and playbooks
ā¢ Build/maintain data infrastructure (reporting layer data pipelines, reports, dashboards, alerts) to monitor the performance of our operations and drive business understanding
ā¢ Proactively propose creative technical and quantitative solutions to problems and drive these through to implementation e.g. Through identification of data &; tooling requirements enabling self-service / scalable solutions
ā¢ Communicate results of analyses to non-technical stakeholders who are the users of systems involving metrics, pipelines, and dashboards
ā¢ Define metrics/KPIs for end-to-end product operations and building repeatable and reproducible analysis
Skills:
ā¢ End to end Dashboarding/ETL Pipeline developments within the product operations space
ā¢ Proficiency with intermediate to advanced SQL concepts for data extraction. Experience creating dashboards with Tableau, PowerBI, Alteryx and other data visualization tools.
ā¢ Experience with communicating and presenting findings to non-technical stakeholders.
ā¢ Big Tech experience
ā¢ Experience measuring the performance of AI models
Education/Experience:
ā¢ Bachelor's Degree in a technical or research-oriented field such as engineering, data science, social science, or related fields, or equivalent practical experience.
ā¢ 4+ years of experience in strategy, operations, consulting, statistics, data analysis, or data science or directly related fields.
ā¢ Proficiency with intermediate to advanced SQL concepts for data extraction.
ā¢ Experience in managing multiple projects and meeting deadlines in a fast-paced environment.
ā¢ Experience creating dashboards with Tableau, PowerBI, Alteryx and other data visualization tools.
ā¢ Experience with statistical analysis, including hypothesis testing, regression, and experimental design.
ā¢ Experience with communicating and presenting findings to non-technical stakeholders.
ā¢ Advanced technical degree or graduate degree in statistics, marketing, or related fields.
ā¢ Experience measuring the performance of AI models
ā¢ Experience with ETL pipeline development.
ā¢ Partner with teams within Product Operations, the broader Global Operations organization, Data Science, Data Engineering, Product and Engineering teams to solve problems and identify trends and opportunities
ā¢ Independently analyze data, conduct research, and synthesize feedback into plans, processes, and playbooks
ā¢ Build/maintain data infrastructure (reporting layer data pipelines, reports, dashboards, alerts) to monitor the performance of our operations and drive business understanding
ā¢ Proactively propose creative technical and quantitative solutions to problems and drive these through to implementation e.g. Through identification of data &; tooling requirements enabling self-service / scalable solutions
ā¢ Communicate results of analyses to non-technical stakeholders who are the users of systems involving metrics, pipelines, and dashboards
ā¢ Define metrics/KPIs for end-to-end product operations and building repeatable and reproducible analysis
Skills:
ā¢ End to end Dashboarding/ETL Pipeline developments within the product operations space
ā¢ Proficiency with intermediate to advanced SQL concepts for data extraction. Experience creating dashboards with Tableau, PowerBI, Alteryx and other data visualization tools.
ā¢ Experience with communicating and presenting findings to non-technical stakeholders.
ā¢ Big Tech experience
ā¢ Experience measuring the performance of AI models
Education/Experience:
ā¢ Bachelor's Degree in a technical or research-oriented field such as engineering, data science, social science, or related fields, or equivalent practical experience.
ā¢ 4+ years of experience in strategy, operations, consulting, statistics, data analysis, or data science or directly related fields.
ā¢ Proficiency with intermediate to advanced SQL concepts for data extraction.
ā¢ Experience in managing multiple projects and meeting deadlines in a fast-paced environment.
ā¢ Experience creating dashboards with Tableau, PowerBI, Alteryx and other data visualization tools.
ā¢ Experience with statistical analysis, including hypothesis testing, regression, and experimental design.
ā¢ Experience with communicating and presenting findings to non-technical stakeholders.
ā¢ Advanced technical degree or graduate degree in statistics, marketing, or related fields.
ā¢ Experience measuring the performance of AI models
ā¢ Experience with ETL pipeline development.