Nextdoor

• Be the voice of the community in the rooms where it counts. • Turn results into action. • Manage and develop a team. • Manage and improve AI-powered community systems. • Co-own Trust & Safety and Community Health initiatives. • Continue building the community's organizational standing. • Strengthen and scale the Neighborhood Leads program globally. • Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises. • Build in-person relationships with team members and contribute to Nextdoor’s company culture.

Analyze and develop compliance plans for privacy laws, draft necessary reports, advise teams on user inquiries, and maintain essential documentation while collaborating across departments to address legal risks effectively.

• Design and develop algorithms and models to optimize Search relevance, retrieval, and ranking • Experiment design: ensure we run experiments efficiently and accurately • Develop and share key strategic insights through data analysis • Build scalable metrics and dashboards to track Search performance • Partner with cross-functional teams to support product development efforts • Care deeply about data quality

• Design and develop algorithms and models to optimize Search relevance, retrieval, and ranking • Experiment design: ensure we run experiments efficiently • Develop and share key strategic insights through data analysis • Build scalable metrics and dashboards to track Search performance • Partner with cross-functional teams to support product development efforts • Care deeply about data quality

• Join a focused team of developers, product managers, and designers • Make key contributions across our iOS stack, developing networking, analytics, experiments, and modular app structure • Collaborate with product managers and designers to drive Nextdoor forward • Mentor other team members and grow your role towards your passions

• Provide technical guidance towards the development and improvement across data processing, APIs, attribution modeling, privacy, billing and other third party integrations • Build a high performing engineering organization and foster a culture of excellence and continuous improvement • Partner and negotiate across engineering, product, legal, privacy and sales teams on strategy and execution

• Define and own the vision and roadmap for campaign optimization, including bidding algorithms, pacing systems, auction dynamics, and automation capabilities • Partner with Data Science, Engineering and ML to shape experimentation strategy, define model success criteria, and translate model performance into advertiser value • Develop and own advertiser experience for campaign delivery optimization features that reduce friction and improve advertiser outcomes • Collaborate with Sales and Product Marketing to ensure optimization capabilities are intuitive, explainable, and compelling to advertisers • Influence cross-functional alignment on tradeoffs between short-term performance gains and long-term architectural investments • Present strategy, impact, and performance insights to senior leadership, serving as the strategic voice for Ads Optimization across the organization • Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises • Build in-person relationships with team members and contribute to Nextdoor’s company culture

• 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

• Own the end-to-end marketing event path from Flask and other product sources into Segment and downstream tools (Iterable, Workato, and other destinations) • Maintain and evolve the mapping engine configuration that filters product events into a canonical Segment CDP topic, ensuring only marketing-relevant traffic flows into the MarTech stack • Build and maintain marketing data pipelines from product events and warehouse models into Segment and Iterable, so lifecycle programs have the right signals for retention, reactivation, and upsell/cross-sell at scale • Own and operate key reverse ETL / bridge jobs from Databricks to Segment and Iterable, ensuring warehouse models and traits stay aligned with marketing requirements and data retention guidelines • Own Segment workspaces, schemas, and destinations for key marketing projects, ensuring events and traits remain organized, documented, and discoverable for marketers and analysts • Manage Iterable integrations for lifecycle and advertiser journeys, ensuring reliable delivery of both real-time event streams and batch traits to support onboarding, reactivation, and upsell programs • Partner with CIA, Sales, and Marketing to design and maintain first-party audiences and interest segments exposed across GAM, internal tools, and email programs • Work with RevOps and DS to replace fragile Salesforce→Iterable syncs with governed Databricks→Iterable datasets — enabling self-serve audience building and reducing manual CSV workflows — including Smart Ingest/Data Sync configurations and governance models for enterprise/NAM accounts • Monitor Segment usage (unique event names, schema growth) and drive consolidation, archival, and naming clean-up to keep the system performant and usable • Ensure identifier consistency across B2B and B2C use cases and alignment with Salesforce, product Identity, and other revenue systems • Maintain data hygiene and PII/consent standards across Segment, Iterable, and related rETL models - including hands-on troubleshooting of consent flows, preference center syncs, and suppression logic to ensure compliance policies hold up in production, not just on paper • Contribute a MarTech perspective to broader governance frameworks (SOX, GDPR/CCPA, global consent patterns) as they apply to marketing data and activation • Serve as the primary MarTech point of contact for Growth Marketing, Lifecycle, Product Marketing, and RevOps on data and tooling questions, incident triage, and new program enablement • Translate marketing requirements into clear data and integration work: events to instrument, traits to model, journeys to support, and QA plans before launch • Partner closely with Data Platform, CXE, Analytics, and BizTech Revenue Systems on cross-system initiatives (e.g., preference centers, consent flows, NEXT launch, international programs) that depend on reliable MarTech infrastructure • Own monitoring and health checks for key pipelines: Kafka write rates, consumer lag, Segment delivery latency, Iterable ingestion health, and Salesforce event flows that impact campaigns and journeys • Lead investigation and resolution for missing, mis-routed, or malformed events and traits, following an end-to-end debugging flow from product events through Segment, Iterable, and audience membership • Act as a first or second-line responder when journeys misfire, audiences change unexpectedly, or campaigns are blocked due to data issues, coordinating with engineering and data teams as needed • Contribute to the MarTech roadmap with a focus on identity hygiene, schema standardization, deliverability, and reducing manual workflows in favor of governed Databricks→Iterable paths • Help evaluate and right-size vendor contracts and platform usage (e.g., Segment, Iterable, Litmus), balancing capability needs with cost and performance. • Maintain and enhance documentation and reference artifacts (e.g., Segment ingestion & architecture docs, User Traits master sheets, role overviews) so the broader team can self-serve and new hires can ramp quickly

• 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.