Nextdoor

Accounting Manager

• Own and maintain revenue accounting policies under ASC 606 in partnership with Technical Accounting
• Lead the monthly revenue close process, including journal entries, revenue analysis, and review of commission calculations
• Analyze billing and revenue activity to identify discrepancies, customer billing issues, or operational risks and ensure timely resolution
• Serve as Accounting’s lead partner on cross-functional initiatives with Product, Engineering, and Business Systems, particularly related to our self-serve payments business
• Support new product launches, customer migrations, and related reporting and revenue processes
• Design scalable reconciliation processes and improve ledger maintenance and financial accuracy
• Partner with Finance & Strategy to provide insight into revenue trends and support forecasting
• Prepare and review revenue-related materials for external audits and SOX compliance
• Identify process inefficiencies and drive improvements through automation, systems enhancements, and better workflows

Revenue & Monetization Accounting Manager

Product Manager

• Lead the strategy and roadmap for how campaigns deliver performance at scale.
• Define and evolve bidding systems, budget pacing frameworks, delivery optimization, and intelligent automation capabilities.
• Partner deeply with Engineering, Data Science, and Revenue teams to shape auction, pacing, and ML-driven optimization systems.
• Develop and own advertiser experience for campaign delivery optimization features.
• Collaborate with Sales and Product Marketing to ensure optimization capabilities are intuitive and compelling to advertisers.
• Present strategy, impact, and performance insights to senior leadership.

Staff Product Manager, Ads Optimization

Data Scientist

• Analyze large, complex datasets to identify abuse patterns, fraud signals, and harmful behavior trends.
• Conduct root cause analysis to diagnose safety incidents and emerging risks.
• Evaluate new tool effectiveness (including AI), and impact on agent efficiency and user satisfaction.
• Define and track core metrics (e.g., harm prevalence, violation rates, detection accuracy).
• Navigate the tradeoff between operational efficiency, safety, and user growth/experience.
• Build dashboards and reporting frameworks to track platform health and safety performance.
• Develop heuristics, statistical models, and machine learning solutions for proactive detection of abuse, fraud, or harmful content
• Build prediction systems (e.g., anomaly detection, risk scoring, behavioral profiling).
• Improve automated enforcement and moderation workflows.
• Evaluate model performance and iterate on detection strategies.
• Design and analyze experiments (A/B tests, causal inference) to measure safety feature impact (e.g., login & verification, AI moderation support). Clearly communicate findings to technical and non‑technical stakeholders.
• Quantify tradeoffs between operational efficiency, safety, and user growth/experience. Guide TnS team on key tradeoffs in decision-making
• Partner with Product, Engineering, Operations, Policy, and Legal teams to define safety strategy.
• Influence decision-making through data storytelling and insights.
• Standardize analytical methodologies and tools for scalable decision-making.

Senior Data Scientist – Fraud Prevention

• Developing, communicating, and leading execution of the data science strategy across Nextdoor’s monetization products
• Owning the monetization DS roadmap: identify the highest-impact opportunities and risks, define clear success metrics, and align stakeholders on priorities
• Raising the bar on DS craft excellence: establish standards for strong analysis, experimentation, and impact-orientedness; provide high-quality review and mentorship; and help the team deliver work that is rigorous, decision-relevant, and well-communicated
• Being a hands-on technical leader: contribute on the framing and execution of the most strategic, ambiguous, and high-leverage problems (e.g., measurement strategy for new products, experiment design standards, causal questions, marketplace dynamics)
• Driving experimentation and measurement: design and evaluate experiments, ensure sound interpretation, and strengthen the end-to-end measurement system (instrumentation, definitions, dashboards, and decision forums)
• Partnering cross-functionally to move strategy forward: serve as a thought partner to Product, Engineering, Sales, and other functions—bringing clarity, structure, and constructive data-informed judgment, especially when tradeoffs are complex
• Building scalable systems and leverage: improve team throughput through reusable frameworks (metric definitions, analysis templates, audience definitions, and tooling) and by reducing repeated, one-off work
• Leading, growing, and developing the team: hire and develop data scientists, create an inclusive and high-performing culture, and ensure strong career growth and performance coaching
• Representing Data Science and a data-informed POV in leadership discussions: communicate clearly to varied audiences—from deep technical reviews to executive narratives—while maintaining rigor and intellectual honesty

Revenue & Monetization Accounting Manager

Staff Product Manager, Ads Optimization

Senior Data Scientist – Fraud Prevention

Head of Data Science – Monetization