Data Scientist

6 days ago

Menlo Park, California, United States Meta Full time
Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click "Apply to Job" online on this web page.

Responsibilities
Perform large-scale data analysis and develop effective statistical models for segmentation, classification, optimization, time series analyses, etc. Define key business metrics, implement dashboards to track goals and KPIs, and translate outputs into actionable insights. Identify testable hypotheses and provide evidence-based recommendations to cross-functional product groups, and influence the direction of the business by communicating results effectively to senior leadership. Continuously improve on tools, techniques, and data infrastructure. Prioritize strategic opportunities through gap and impact analyses, and build forecasting models to guide teams to focus on the most valuable projects.

Qualifications
Master's degree (or foreign degree equivalent) in Computer Science, Mathematics, Economics, Statistics, or related field, and 12 months of experience in the job offered or a related occupation Requires 12 months of experience in the following: Qualitative analysis, including content analysis, competitive analysis, and phenomenology Quantitative analysis, including clustering and regression techniques, pattern recognition, descriptive and inferential statistics, and experimental design, including hypothesis testing in an industry setting Practical experience using querying (e.g. SQL) and scripting (e.g. Python) languages to orchestrate Extract, Transform, and Load (ETL) processes on large-scale relational databases, and performing data mining on highly-complex datasets for the aforementioned analyses Performing structured audits of data loggers and pipelines to recommend infrastructural improvements , and guiding internal teams to prioritize highest impact work based on top business
needs Presenting qualitative and quantitative information to technical and non-technical audiences, including the application of machine learning techniques and Artificial Intelligence (AI) within the company's products

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