Senior Data Science Manager, Discord

• 3+ years managing and developing data science or analytics teams, including managing managers or leading teams of 5+
• 6+ years of industry experience applying analytics to ambiguous product and business problems
• Expertise in product analytics, experimentation/A‑B testing, and product strategy
• Strong communication skills. Able to translate complex analyses into clear narratives for technical and non‑technical audiences
• Proficiency in SQL and competence with Python or R for hands‑on analysis when needed
• Fluency with A/B testing principles and common pitfalls. Comfortable with metric design and interpretation
• Working knowledge of modern BI tools such as Looker or Tableau. Strong eye for compelling, performant data visualization
• Collaborative, low‑ego, and user‑obsessed. Bias to action and learning

Desirable

• Discord gives people the power to find belonging
• Our Core Product teams build the features hundreds of millions of people use to talk, play, and hang out together
• We are looking for a Senior Data Science Manager to lead analytics for Core Product, partnering closely with Product, Engineering, Design, and go-to-market teams to shape strategy, ship great experiences, and measure impact
• Scale of impact: Your work will influence decisions that touch hundreds of millions of users worldwide
• Team leadership: You will grow and mentor a high-performing team of Analytics Data Scientists and raise the bar for data at Discord. You will serve as one of the leads for the cross-functional Core Product org
• Lead, mentor, and grow a mission‑driven team of Analytics Data Scientists. Create a culture of excellence, curiosity, and impact
• Own the analytics vision and roadmap for Core Product, aligning with company strategy and product goals
• Partner with PM, Eng, and Design to create strategies, identify opportunities, shape hypotheses, and prioritize the highest‑leverage work
• Define clear, interpretable metrics that reflect user value and product health. Establish guardrails and diagnostic views
• Design rigorous experimentation and quasi‑experimental approaches. Set standards for test design, power, and interpretation
• Drive strategic analyses that inform product bets, roadmap tradeoffs, and long‑term strategy
• Build scalable, self‑serve tools, dashboards, and data models that enable decision‑making at all levels
• Improve operating cadence: lightweight processes, crisp prioritization, and clear decision records
• Contribute to data org best practices across architecture, governance, documentation, and knowledge sharing