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