Data Analyst II

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. Build/maintain data infrastructure (reporting layer data pipelines, reports, dashboards, alerts) to monitor the performance of our operations and drive business understanding. Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains Independently analyze data, conduct research and synthesize feedback into plans, processes and playbooks Proactively propose creative technical and quantitative solutions to problems and drive these through to implementation e.g. thorough 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 Utilize AI tools to help automate routine analyses and scale solutions. Skills:

Experience in strategy, operations, consulting, statistics, data analysis, or data science or directly related fields. Experience with ETL pipeline development. 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, Power BI, 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. Experience using AI for data analysis and summarization Experience measuring the performance of AI models Experience working across time zones and with diverse audiences, including within operations teams and across with key stakeholders and senior leadership Experience with ETL pipeline development. Proficiency with intermediate to advanced SQL concepts for data extraction. 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 Experience using AI for data analysis and summarization. Experience measuring the performance of AI models Experience working across time zones and with diverse audiences, including within operations teams and across with key stakeholders and senior leadership 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.