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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.
Job Responsibility:
Perform large-scale data analysis and develop effective statistical models for segmentation, classification, optimization and prediction to drive key product OKRs
Develop and code software programs and algorithms to automate analysis, build pipelines, maintain and scale large datasets and models
Improve product and drive value for customers by understanding ecosystems, user behavior and long-term trends
Influence cross-functional partners like Product & Engineering as well as the direction of the business by identifying actionable insights, trends and anomalies through data analysis and/or design and implementation of dashboards
Requirements:
Master’s degree (or foreign degree equivalent) in Computer Science, Mathematics, Economics, Statistics or related technical field
Completion of one university-level coursework, research project or internship must include experience in: Designing, executing and evaluating complex experiments
formulating and testing hypotheses to inform product strategy
Utilizing Quantitative analysis techniques (e.g., clustering, regression, pattern recognition, descriptive and inferential statistics) to influence product decisions and direction
Predicting and forecasting outcomes through the application of quantitative methodologies, with an understanding of how changes may have or did impact these outcomes
Developing analytical designs that span the analytic process, including cleaning, structuring & weighting data as appropriate, combining multiple data types, writing statistical software code and interpreting outputs
Identifying appropriate data collection tools, techniques, or methods to be used for a specific research problem