• Collaborate closely with the User Acquisition team to optimize Paid Social campaign performance. • Own the technical frameworks for tracking marketing effectiveness in a privacy-first world. • Own the end-to-end design and maintenance of marketing analytics dashboards in BI tools. • Conduct granular analysis on campaigns and creative performance with data-driven recommendations. • Deeply analyze mobile user cohorts to understand retention and monetization behaviors. • Collaborate with marketing and finance team members for channel incrementality measurement.

• Own and execute the technical roadmap for data science models and scalable, production-grade data products. • Lead cross-functional initiatives end-to-end—from problem definition through launch—driving clear milestones, accountability, and high quality standards. • Act as a true peer partner to Engineering, Product and Design, aligning on technical strategy, architectural decisions, and long-term roadmaps. • Lead teams responsible for developing, validating, and productionizing models, working closely with Engineering to ensure the right data sources, pipelines, and APIs are in place. • Hire, mentor, and develop top talent while continuously raising the bar through rigorous reviews, coaching, and feedback. • Deeply understand customer pain points and desired outcomes; turn them into clear technical requirements and DS solution designs. • Recommend and translate statistical outputs and data science models into customer-facing features and enterprise solutions. • Establish repeatable validation processes for model release and collaborate with Data Engineering to ensure data quality and robust edge-case handling.

• Develop and own the forward-looking roadmap for AI, advanced data science, and predictive modeling • Identify and prioritize opportunities where AI can create new value and fundamentally accelerate business processes • Lead the design, development, and implementation of cutting-edge AI solutions • Act as the primary AI evangelist and partner to C-suite executives and senior business leaders • Model & Platform Governance: Oversee the full lifecycle of our predictive models and AI systems, from conception and training to deployment, monitoring, and continuous improvement

• Define multiyear DS/ML strategy and prioritize a cross-team roadmap • Build and scale a high-performing team of cross-functional experts • Ship reliable real-time and batch models • Establish model governance, documentation, and observability • Stand up on-call practices, incident response, post-mortems, and SLOs • Scale an experimentation program with clear guardrails • Set credible and inspiring long-term research direction for data scientists • Align with Product, Risk/Trading, Marketing, and Compliance