Data Scientist

Meta · Big Tech · Menlo Park, CA

Meta is seeking a Data Scientist to perform large-scale data analysis, develop statistical models for segmentation, classification, optimization, and prediction to drive product OKRs. The role involves coding software programs and algorithms to automate analysis, build pipelines, and manage large datasets and models. Responsibilities include understanding user behavior, influencing cross-functional partners, identifying insights through data analysis, and designing dashboards. Qualifications include a Master's degree in a technical field with experience in experimental design, quantitative analysis techniques, and predictive modeling.

What you'd actually do

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.

Skills

Required

Master's degree (or foreign degree equivalent) in Computer Science, Mathematics, Economics, Statistics or related technical field
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

What the JD emphasized

Designing, executing and evaluating complex experiments
Utilizing Quantitative analysis techniques
Predicting and forecasting outcomes

Read full job description

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 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.

Qualifications

Requires a 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 the following: 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, AND Identifying appropriate data collection tools, techniques, or methods to be used for a specific research problem