Competitive Intelligence Research

About the role

As a Senior Analyst in Meta’s Competitive Intelligence organization, you will operate at the intersection of advanced analytics, data science, and market strategy. You will lead major projects and product areas—often in environments of significant ambiguity or technical complexity—driving both technical and business outcomes. This is a hands-on, high-impact role for builders who thrive on solving real problems. The role demands a unique blend of analytical and statistical expertise, strategic thinking, and the ability to translate complex insights into impactful product and business decisions. You will be recognized as a thought partner by cross-functional leads and will help shape the analytical foundations that inform how we build and grow our products.

Responsibilities

• Market Strategy: Influence organization-level product direction through data-driven narratives and an in-depth understanding of the market landscape. Demonstrate experience operating at scale and across ambiguous environments with working knowledge of econometrics. Blend practical and applied understanding with technical expertise, including pressure-testing data for quality, reliability, understanding data biases, and being solution-driven.
• Analytics Leadership: Conduct advanced analyses with third-party datasets, develop statistical models and forecasts, and deliver actionable insights that inform market and business strategy. Responsibilities include:
  • Data onboarding: Identify, onboard, and rigorously evaluate third-party datasets to determine their signal-to-noise ratio and predictive power.
  • Data triangulation: Triangulate data from many sources of imperfect information. Synthesize multiple, low-fidelity third-party signals into a single high-fidelity trend report using Bayesian aggregation or other methods.
  • Data transformation: Apply quasi-experimental designs (e.g., synthetic control, diff-in-diff) to isolate the impact of exogenous market shocks and competitor actions on internal performance metrics, using third-party behavioral and economic datasets.
  • Insight and implications: Apply guidance from such analyses to increase the accuracy of forecasts and better understand market trends.
• Technical & Methodological Expertise: Act as a recognized professional in a technical or methodological area (e.g., causal inference, Bayesian aggregation), driving the adoption of advanced methods and organization-wide best practices that raise the bar for the entire team.
• Data Governance & Quality: Ensure data privacy, security, and compliance with organizational standards. Champion data quality frameworks and documentation practices that enable credible, reproducible analyses.
• Be a resourceful, adaptable professional with a bias for action.

Requirements

• Bachelor’s degree and a minimum of 6 years of work experience (minimum of 4 years with a Ph.D.) in business intelligence, product analytics, or economic or strategy consulting in a technology environment with increasing scope and impact.
• Demonstrated skill to ethically source, validate, and synthesize high-signal insights from people (e.g., stakeholder interviews, skilled conversations, field research, and relationship-based information gathering) while maintaining high standards for privacy, consent, and integrity.
• Proficiency in AI-powered tools: Demonstrate working knowledge of Generative AI technologies (e.g., LLM and AI agents) and experience designing, prompting, and orchestrating AI systems (e.g., prompt engineering) to automate data analyses, synthesize insights, and execute multi-step analytical tasks (e.g., prompting an agent to clean datasets, build visualizations).
• Practical working understanding of data-analytics tools, and direct experience managing, analyzing, manipulating, and interpreting first-party and external third-party datasets.
• Experience with data querying languages (e.g., SQL), scripting languages (e.g., Python), and/or statistical/mathematical software (e.g., R).
• Proven experience with statistical analysis including causal inference (e.g., randomized control trials, quasi-experimentation such as synthetic control, diff-in-diff, meta-analyses), and/or Bayesian aggregation (e.g., Bayesian pooling, hierarchical modeling).
• Demonstrated communication skills and experience presenting complex findings to both technical and non-technical stakeholders.
• Demonstrated experience thriving in ambiguous environments and shaping new analytics organizations or products.

Preferred Qualifications

• Master’s or Ph.D. Degree in a quantitative field such as Quantitative Economics or Political Science, Operations Research, Data Science, Computer Science, Physics, Business, or Mathematics.
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements).
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews).
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies.

About Meta

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps 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.

Pay

$177,000/year to $247,000/year + bonus + equity + benefits. Individual compensation is determined by skills, qualifications, experience, and location.