• Own end-to-end modelling of LTV, user segmentation, retention, and marketing efficiency to inform media optimization and value attribution. • Collaborate with Paid Media and RevOps to optimize SEM performance, predict high-value cohorts, and power strategic bidding and targeting. • Work closely with Product Insights and General Managers (GMs) to define core metrics, KPIs, and success frameworks for new launches and features. • Conduct deep-dive analysis of user behaviour, funnel performance, and product engagement to uncover actionable insights. • Monitor and explain changes in key product metrics, identifying root causes and business impact. • Work closely with Data Engineering to design and maintain scalable data pipelines that support machine learning workflows, model retraining, and real-time inference. • Build predictive models for conversion, churn, revenue, and engagement using regression, classification, or time-series approaches. • Identify opportunities for prescriptive analytics and automation in key product and marketing workflows. • Support development of reusable ML pipelines for production-scale use cases in product recommendation, lead scoring, and SEM planning. • Present insights and recommendations to a variety of stakeholders — from ICs to executives — in a clear and compelling manner. • Translate business needs into data problems, and complex findings into strategic action plans. • Work cross-functionally with Engineering, Product, BI, and Marketing to deliver and deploy your work.

• Directly manage a 6-person Analytics Data Science team across junior to senior levels, providing right-sized coaching, feedback, and development support. • Participate in Safety Leads group, building strong cross-functional relationships and contributing data-driven perspectives to safety strategy. • Ensure quality of deliverables across the team through direct review or delegation to senior team members, maintaining and improving existing processes. • Up-level the team’s ability to have more strategic impact by improving processes, stakeholder management, and driving ruthless prioritization. • Develop your own strategic point of view of how Safety can be improved at Discord and drive change via thought leadership and/or deliverables from your team.

• Understand clients' businesses and translate their needs into data-driven and generative AI solutions • Implement and operationalize models using MLOps practices and tools such as Ollama • Explore and assess datasets to create efficient and robust pipelines • Build generative AI applications using LLMs, AI agents, and frameworks such as LangGraph and CrewAI • Produce strategic insights and communicate them clearly, supporting decision-making through data storytelling

• As a Senior Data Scientist, Product Analytics, you will build the analytics foundation enabling fast, confident, and measurable decisions. • Own the full product analytics lifecycle: defining product success metrics, shaping instrumentation strategies, building canonical datasets, etc. • Partner closely with Product and Engineering to embed analytics into every release. • Define the questions, build frameworks to answer them at scale, and help operationalize Product Analytics as a core capability.