meta is hiring for product growth analyst and data science roles across united states, these roles focus on product analytics, user growth, and data driven decision making. usa and international candidates are eligible to apply
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as a product growth analyst, you will analyze user behavior and product performance. the role supports growth experiments, feature adoption, and business strategy, uses data science to drive decisions across its global products.
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candidates with backgrounds in data science, statistics, economics, or engineering (STEM) can apply, both entry leval and early career analysts are considered for job role.
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strong knowledge of sql is required to analyze large scale product datasets, mostly python or R is used for data analysis, experimentation, and AI automation. these skills are essential for most US based analytics roles.
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you will work with growth metrics like retention, engagement, churn, and conversion, understanding funnels and cohort analysis helps identify growth opportunities.
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tools like power BI, tableau, looker, or internal dashboards are used to present insights, clear data storytelling helps product managers make faster decisions
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international candidates on F1 visa with OPT or STEM OPT eligibility may apply & CPT experience can be relevant where permitted, H1B transfer or sponsorship depending on role requirements and eligibility.
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basic of machine learning concepts such as predictive analytics, customer modeling, and risk scoring is important,frameworks like scikit-learn, tensorflow, pytorch, and cloud ml platforms are widely used in meta
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ML is widely used in fraud detection, credit risk modeling, and transaction monitoring, is widely used in fraud detection, credit risk modeling, and transaction monitoring
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Knowledge of generative ai concepts and large language models such as gpt, llama, and gemini is increasingly valued, tool like hugging face, langchain, vector databases, & retrieval augmented generation is like cherry on cake.
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modern data science roles use cloud platforms like aws sagemaker, azure machine learning, and google vertex ai for model training & deployment, these platforms support scalable ml pipelines, experimentation, and production workflows.
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meta builds large scale recommendation algorithms to personalize feeds, ads, and content discovery, these systems use machine learning techniques such as ranking models, collaborative filtering, and real time prediction.
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the role requires working with real time data systems to process streaming events at scale and low latency machine learning models are used to generate instant predictions and personalized responses.
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the role involves designing and refining prompts to guide large language models toward accurate and consistent outputs, prompt engineering is used to support analytics, content ranking, automation, and decision workflows.
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the role requires clear communication of analytical ai driven insights to cross functional stakeholders, complex findings must be translated into simple recommendations for product, business, and leadership teams.
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