Staff Data Scientist - Ads Marketplace

#TeamNextdoor

Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com.

Meet Your Future Neighbors

As a Data Scientist at Nextdoor, you will help design and oversee product experiments and own complex analyses to drive company and product strategy. We use a semi-embedded team structure, in which a group of data team members works on a specific product or pillar, interfacing directly with product and engineering stakeholders. The Data Science group consists of people from a diverse set of backgrounds and perspectives, trained in fields as wide-ranging as economics, physics, statistics, and operations research. We are an integral part of the product development organization and play an active and collaborative role in building and improving the product.

At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. 

We also offer a warm, inclusive work environment that embraces a hybrid employment model and provides flexibility 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.

The Impact You’ll Make

We're looking for a Staff Data Scientist to lead data science for Ads Marketplace/Delivery. Delivery sits at the heart of the marketplace. It decides which ads are shown, to whom, at what price, and how pacing, budgets, and auction mechanics balance advertiser value, user experience, and platform revenue.

As the go-to expert on how our marketplace behaves and how to improve it, this person shapes the roadmap with Engineering, Product, and ML leadership and sets the bar for how delivery changes are designed, measured, and shipped.

Your responsibilities include:

• Serve as the technical lead for ads delivery data science, driving the roadmap across ads delivery areas (auction score development, budget pacing, bidding and optimization, etc.) 
• Set the standard for experimentation in a two-sided marketplace, tackling interference, spillovers, and long-term effects, and advancing methods and causal approaches where standard A/B tests fall short.
• Partner with ML engineers on ranking, bid optimization, and pacing models by shaping objectives, offline evaluation, and the link between offline metrics and online outcomes.
• Lead deep-dive analyses that surface opportunities and diagnose delivery issues, such as supply and demand imbalances, auction dynamics, reserve and floor pricing, and advertiser spend patterns.
• Influence product strategy by translating complex findings into clear recommendations for senior leaders and cross-functional partners.
• Mentor data scientists and raise the bar for analytical rigor across the ads org.

What You’ll Bring To The Team

• Ph.D. or M.S. in Economics, Operations Research, Statistics, Computer Science, Applied Mathematics, or related quantitative fields.
• 10+ years of relevant Data Science experience in Ads Marketplace or Monetization experience
• Expert knowledge of SQL and Python programming, including common scientific computing packages and data science tools such as numpy, pandas, and scikit-learn
• Excellent communication skills, with the ability to synthesize, simplify, and explain complex problems to different types of audiences, including executives, and compile compelling narratives
• Deep expertise in statistical inference, advanced experimental design, and quantitative economic modeling.
• Experience with ML-driven ads systems (CTR/CVR prediction, bid optimization, budget allocation)
• Eagerness to explore and apply AI and emerging technologies to reimagine how work gets done

Nice to Have

• Familiarity with simulation, forecasting, or optimization techniques for marketplace design.
• Experience with local, social, or performance advertising products.
• Experience mentoring data scientists and building analytical culture.

Rewards

Compensation, benefits, perks, and recognition programs at Nextdoor come together to create our total rewards package. Compensation will vary depending on your relevant skills, experience, and qualifications.

The starting salary for this role in the San Francisco area is expected to range from $190,000 to $283,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. The salary range will be determined by the candidate’s geographic location.

We expect to award a meaningful equity grant for this role. With quarterly vesting, your first vest date will take place within 3 months of your start date.

When it comes to benefits, we have you covered! Nextdoor employees can choose between a variety of health plans, including a 100% covered employee-only plan option, and we also provide a OneMedical membership for concierge care.

At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we serve. We encourage everyone interested in our mission to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.

For information about how we collect and use applicants’ personal information, please see Nextdoor's Personnel Privacy Notice, found here.