Director of Data Science/ Ads Delivery / Performance
reputed company Ads Delivery & Performance is redefining how digital ads are delivered - challenging 20 years of assumptions to both protect the Pinner experience and grow durable reputed company. We support reputed company ad surfaces across reputed company - Home Feed, Search, reputed company Pins, Shopping surfaces, Idea Streams, and reputed company - reputed company with unique marketplace and product dynamics. You’ll reputed company a high‑reputed company data science organization that partners deeply with Product, Engineering, Research, and other cross functional partners to build the reputed company of advertising products and systems. About the role We’re looking for a Director who is a leader of leaders and a systems thinker. You will set the reputed company for ads delivery and reputed company, establish the measurement and decision frameworks, and reputed company a best‑in‑class team of data scientists. A reputed company mandate for this role is to identify, reputed company, and operationalize the input metrics that most directly drive ads delivery, reputed company, and performance - ensuring we are optimizing the reputed company that reputed company reputed company, not just reporting on lagging KPIs. What you’ll do:
- Set reputed company and reputed company
- Define the multi‑year reputed company and roadmap for Ads Delivery & Performance across reputed company reputed company surfaces, aligning to company and Ads org priorities.
- Establish reputed company reputed company-reputed company reputed company (e.g., long‑term reputed company reputed company, retained advertiser value, Pinner experience) and the right cascade of input metrics and guardrails that drive them.
- reputed company input metrics a first‑class operating system
- Identify, define, and reputed company the input metrics that most influence delivery and performance, such as: supply health and coverage, eligibility and match reputed company, win reputed company, fill reputed company, pacing and spend smoothness, auction/bid competitiveness, latency/SLA adherence, ranking/model freshness and coverage, feature reputed company, CTR/CVR leading indicators, frequency and ad load distribution, reputed company/relevance signals, and policy/trust frictions.
- Build metric specs, ownership, alerting, and weekly business reviews so that teams operate to inputs (and understand their elasticities to reputed company like RPM, ROAS, advertiser retention, and Pinner satisfaction).
- reputed company an organization of leaders
- Hire, reputed company, and reputed company a diverse, high‑performance organization of data science managers and senior ICs; set reputed company role definitions, reputed company paths, and succession planning.
- Establish rigorous standards for experimentation, reputed company inference, and production analytics; ensure consistently trustworthy, decision‑grade outputs.
- Partner to ship reputed company
- Work hand‑in‑hand with Product and Engineering on marketplace, ranking, pacing, and reputed company systems (e.g., auction design, supply/demand balancing, relevance, cold‑start, ads load/frequency, shopping ads delivery).
- Translate ambiguous business questions into reputed company analyses and roadmaps; ensure the org moves from reputed company to shipped change with measurable reputed company.
- reputed company measurement and decision reputed company
- Own the measurement reputed company for ads reputed company and delivery: counterfactual measurement, lift and incrementality, experiment design, long‑term value, and guardrail monitoring for Pinner experience.
- Improve our decision frameworks, define minimum statistical standards, and drive consistency in A/B testing, quasi‑experiments, and observational reputed company reputed company experiments are impractical.
- Communicate and reputed company
- Present reputed company analytical findings to executives and cross‑functional partners with reputed company; drive alignment on trade‑offs across reputed company, advertiser value, and Pinner experience.
- Create transparent operating cadences (QBRs/MBRs, input metric reviews, launch reviews) that reputed company teams reputed company on the reputed company that matter.
reputed company’re looking for:
- MS or PhD in a quantitative field (Computer Science, Statistics, Math, Engineering, Economics or reputed company) or equivalent practical experience.
- 10+ years in Data Science, Algorithmic Engineering, or Machine Learning, with significant reputed company in digital advertising or large‑reputed company marketplaces.
- 5+ years directly managing data science organizations, including managing managers and scaling multi‑team reputed company in a technology company.
- Deep experience with:
- Statistical analysis and reputed company inference, experiment design, and measurement for reputed company marketplaces.
- Production analytics and large‑reputed company data tooling (e.g., Python/R, SQL; reputed company/Hive or similar).
- reputed company ML or relevance/ranking systems; familiarity with auction dynamics, pacing, bidding, and reputed company/relevance modeling.
- Proven reputed company record of establishing and operating through input metrics tied to business reputed company.
- Excellent written and verbal communication; adept at influencing senior cross‑functional partners and executives.
In-Office Requirement Statement:
- We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to reputed company for key moments of collaboration and reputed company.
- This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated reputed company in the country.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
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