Head of Data Science - Monetization
NextdoorUS Remote$199k – $300kPosted 4 March 2026
Job Description
<h4><strong>#Team</strong><strong>Nextdoor</strong></h4>
<p>Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and local businesses use Nextdoor to connect around information that matters in more than 340,000 neighborhoods across 11 countries. We build technology that helps people foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at <a href="http://nextdoor.com/"><strong>nextdoor.com</strong></a>. </p>
<h4><strong>Meet Your Future </strong><strong>Neighbors</strong></h4>
<p>As Nextdoor’s Monetization Data Science Lead (Senior Manager/Director), you will be a co-owner in shaping our monetization strategy and outcomes. You’ll also contribute to the broader senior leadership group by helping connect product strategy, business goals, and data-informed direction.</p>
<p>Your work will directly impact how Nextdoor creates value for businesses of all sizes—from multinational brands to the dry cleaner and babysitter down the street—while balancing advertiser outcomes with neighbor experience and long-term platform health.</p>
<p>The Data Science team operates in a semi-embedded model: data scientists are closely aligned to product pillars and work day-to-day with product, engineering, and business stakeholders to drive decision-making through rigorous measurement, experimentation, and modeling. Our team brings diverse backgrounds and perspectives; we act as decision scientists for product development and marketing, and play an active role in building, improving, and evaluating the product and business.</p>
<p>At Nextdoor, we offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. </p>
<h4><strong>The</strong><strong> </strong><strong>Impact</strong><strong> You’ll Make</strong></h4>
<p>In this role, you will be responsible for developing, communicating, and leading execution of the data science strategy across Nextdoor’s monetization products. This leader will set a high bar for the Data Science craft and team effectiveness—combining strong hands-on technical and business judgment with the ability to scale impact through others. While people management and growth are key to this role, it is not a pure management position; strong technical and domain expertise are strongly preferred.</p>
<p>You’ll help build a culture where asking the right questions, high velocity, and proactivity in leveraging data are the norm. This role has the potential to materially influence Nextdoor’s growth trajectory by improving how we identify opportunities, measure progress, and make decisions across monetization.</p>
<p><strong>Your responsibilities will include: </strong></p>
<ul>
<li>Owning the monetization DS roadmap: identify the highest-impact opportunities and risks, define clear success metrics, and align stakeholders on priorities</li>
<li>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</li>
<li>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)</li>
<li>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)</li>
<li>Partnering cross-functionally to move strategy forw ... (truncated, view full listing at source)
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