Meta is seeking a Data Scientist to join our Law Enforcement Analytics & Program (LEAP) team. Our mission is to enable Meta's capacity to balance public safety, user privacy, and compliance obligations at scale through strategic coordination, technical leadership, and operational success across the Security, Integrity, Investigations (SI2) legal team and its partners. This role leverages AI, data and insights to drive decisions that enable predictability, and proactive detection, allowing us to operate efficiently and reliably at scale. You will be building AI models and will be involved in the design, development, and deployment of intelligent solutions that reduce the operational and investigative burden. This role will directly impact the scalability and efficiency of our operations and investigations through proactive detection, automation, and resolution of routine tasks, inefficiencies, and incidents. In addition, this is a crucial role in translating data into action and identifying opportunities for efficiency and effectiveness.
Responsibilities
Translate business challenges into clear, actionable requirements for AI-enabled solutions Map end-to-end business processes, highlighting areas where AI can drive efficiency and value Design, build and implement AI automations Develop and deploy solutions and AI prompts to identify and address bottlenecks, replacing manual interventions with intelligent automation Create scalable automation mechanisms that proactively monitor, analyze, and report Build robust predictive models using statistical and machine learning techniques to forecast risks, anticipate issues and optimize Develop monitoring tools to trigger early warnings and facilitate rapid resolution through automation Acts as a data subject matter Formulate the right metrics, measures, and definitions of success to drive quality, efficiency, cost, and timeliness understanding the source data Perform complex data analysis leveraging data streams available to drive proactive and predictive action Partner with operational analysts, investigators, and engineering partners to understand pain points, identify repetitive tasks, and translate them into opportunities for automation Bring multiple areas of business and engineering together via a common reliable foundation of common data, metrics, and insights Build data tables and dashboards, and leverage these for interpreting incidents and trends Leverage tools like Tableau, Python, and SQL to drive efficient analytics
Qualifications
6+ years of experience in analytics, engineering, and use of AI/ML 6+ years of SQL development experience and scripting language like Python Hands-on experience with AI/ML frameworks (e.g. TensorFlow, PyTorch, Scikit-learn) and automation tools/platforms Experience with data visualization tools and leveraging data models to drive business decisions Experience with statistics (e.g. statistics basics, statistical modeling, experimental design, hypothesis testing, etc.) Demonstrated experience with proactively identifying, scoping and implementing solutions Hands-on experience analyzing and interpreting data, drawing conclusions, defining recommended actions, and reporting results across stakeholders Bachelor's Degree in an anlaytical field (e.g. Computer Science, Engineering, Mathematics, Statistics, or Data Science) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Master's Degree in an analytical field (e.g. Computer Science, Engineering, Mathematics, Statistics, or Data Science)