Назад
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9 дней назад

Staff Product Manager (Personalization)

270 000 - 325 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR
Staff Product Manager (Personalization) (Recommendations/Ranking): Owns shared personalization, fan-understanding, and predictive lifecycle systems for StubHub’s consumer product with an accent on recommendation quality, user modeling, and measurable lifetime-value impact. Focus on designing ranking and experimentation strategies, solving cold-start and freshness challenges, and driving adoption across Search, Discovery, and CRM.

Location: Hybrid, 3 days in office and 2 days remote, in New York, NY or Century City, CA, United States.

Salary: $270,000–$325,000 gross annual base salary, plus equity and benefits.

Company

hirify.global is a global marketplace for buying and selling tickets to live events, serving customers in 195 countries through hirify.global and viagogo.

What you will do

  • Own the multi-year personalization strategy and roadmap across ranking, taste and intent modeling, and predictive lifecycle signals.
  • Define recommendation objectives, signals, evaluation criteria, and product principles for returning fans and visitors with limited history.
  • Build shared personalization capabilities for Search, Discovery, and CRM, including reusable fan profiles and predictive signals.
  • Design experiments and holdouts to measure incremental effects on repeat purchase, frequency, retention, and lifetime value.
  • Lead technical discussions on models, features, pipelines, serving architecture, and adoption by partner teams.
  • Communicate strategy and results to executives and non-technical audiences, mentor PMs, and improve product practices.

Requirements

  • 8+ years of product management experience on consumer web or native mobile products, including at least 3 years owning recommendation, ranking, or personalization systems.
  • Experience shipping ML-powered consumer experiences at scale and explaining their incremental business results.
  • Demonstrated impact on repeat purchase, retention, or frequency in a consumer business.
  • Experience designing holdouts and controlled experiments that isolate incremental effects and inform decisions.
  • Working knowledge of recommendation and ranking systems, user modeling, and supporting data infrastructure.
  • Ability to evaluate models, investigate offline-to-online gaps, and discuss trade-offs with ML engineers and data scientists.
  • Ability to balance multiple product teams and recognize when shared capabilities are more valuable than surface-specific solutions.
  • Strong product judgment around recommendation quality, filter bubbles, cold start, staleness, and user trust.
  • Excellent written and verbal communication, organizational skills, comfort with ambiguity, and ability to manage competing workstreams.

Nice to have

  • Prior ownership of a platform or shared system with internal customers.
  • Experience in live events, ticketing, travel, marketplaces, or commerce with time-limited inventory.
  • Familiarity with lifecycle prediction, purchase propensity, retention risk, or incremental response modeling.

Culture & Benefits

  • Hybrid work schedule with three office days and two remote days.
  • Autonomy to lead large-scale experiments and tests in an accelerated growth environment.
  • Competitive compensation including equity and performance-related upside.
  • Unlimited Flex Time Off, paid parental leave, 401(k), and health, vision, and dental insurance.

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