Pay range: $40-43/hr. on W2 or $50-52/hr. on C2C Work Location: CA-Remote Description: Job Title: Data Analyst Product Operations' focus is to support and educate the people and businesses who use our products through direct interactions and scalable solutions. We develop processes to help improve the health and quality of our products and work with cross-functional partners to ensure a high-quality experience on our platforms. You will gain experience and make an impact in a fast-growing organization. Those who join our teams are very passionate about solving user issues, and are strong advocates for Meta users globally. If you like helping people, Product Operations is for you. The Product Operations team ensures that the Meta suite of apps are as reliable as possible by working closely with Global Operations, Data Science, Engineering, Product and several other teams. We are looking for a data analytics engineer who shares our passion for helping make Meta apps and products reliable and safe. The right candidate will be comfortable in a fast-moving organization and excited to collaborate cross functionally. You will guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions. You will refine our systems, and create scalable data models. Ensuring data security and quality, and with a focus on efficiency, you will suggest architecture and development approaches and data management standards to address complex analytical problems. You will possess strong quantitative analytical skills, statistical knowledge, data visualization skills and communication skills, and the ability to build strong partnerships to drive impact across the organization. Responsibilities Partner with teams within Product Operations, the broader Global Operations and WhatsApp 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.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 Utilize AI tools to help automate routine analyses and scale solutions. Minimum Qualifications Bachelor's Degree in a technical or research-oriented field such as engineering, data science, social science, or related fields, or equivalent practical experience. 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, 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. Preferred Qualifications Advanced technical degree or graduate degree in statistics, marketing, or related fields. 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
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