• Define and drive a clear analytics vision aligned to client engagement, media performance, and marketing measurement priorities. • Champion a data-driven culture by embedding analytics into strategic planning, campaign optimization, and decision-making processes. • Lead the development and execution of measurement frameworks tailored to each client’s objectives, ensuring alignment with business goals. • Translate data into actionable insights by identifying performance drivers, resolving anomalies, and crafting compelling narratives that demonstrate media impact. • Establish and maintain robust testing frameworks that are statistically valid and operationally scalable. • Drive confidence and alignment by delivering actionable insights rooted in analytics, business strategy, and persuasive communication. • Provide business feedback as a key stakeholder in the development of standardized dashboards and advanced analytics to measure the effectiveness of campaigns. • Leverage predictive and prescriptive analytics to identify trends, opportunities, and risks related to client behavior and retention. • Utilize advanced analytics to quantify marketing impact and ROI, and partner cross-functionally to diagnose and address performance irregularities. • Implement robust A/B and multivariate testing and experimentation protocols to optimize campaigns and maximize impact.

• Perform analyses on products to answer open-ended questions and provide strategic recommendations. • Design and guide experiments/analysis to measure impact and drive product improvements. • Develop and maintain key metrics and reports, enhancing data infrastructure for better analysis.

• Conduct analysis and deep dives on ambiguous problems for our business. Your work will result in insights and recommendations that guide the team’s decision making. • Act as owner for a broad scope of data and metrics, from core logging to presentation of data visualizations. • Guide code reviews, provide SQL and Python expertise, and create well-maintained ETL jobs. • Maintain a high bar for statistical rigor on your team. Ensure that we’re conducting experimentation and causal analyses that build confidence with your stakeholders.

• Design, develop, and deploy LLM- and RAG-powered applications that enhance analyst and hacker productivity across offensive security use cases. • Integrate Generative AI models with internal APIs and security datasets to automate and augment workflows. • Build and fine-tune ML models for vulnerability prediction, triage prioritization, and exploit pattern detection. • Develop evaluation pipelines and feedback loops to continuously improve AI model performance and explainability. • Architect and maintain large-scale, high-performance data pipelines to process vulnerability, asset, and activity datasets from multiple sources. • Build secure data ingestion, transformation, and storage workflows leveraging AWS and modern MLOps practices. • Develop robust CI/CD pipelines for data and ML model deployment. • Collaborate with security researchers and engineers to translate offensive security workflows into data-driven automation.