Job Description

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.

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