Principal Product Manager
Content & Distribution
Posted on 2/6/2024
Slickdeals

51-200 employees

Community-driven platform for vetting and sharing deals
Company Overview
Slickdeals, a leading shopping site in the U.S., leverages the power of community and human intelligence to ensure consumers get the best deals, with its 12 million users vetting and voting for top products from renowned retailers. The company has saved its users a staggering $10 billion, demonstrating its significant competitive advantage in the market. Its culture of collaboration, coupled with technical tools like a free app, browser extensions, and a cashback rewards program, make it an engaging and rewarding place to work.
Consumer Goods
Data & Analytics

Company Stage

N/A

Total Funding

N/A

Founded

1999

Headquarters

San Mateo, California

Growth & Insights
Headcount

6 month growth

-1%

1 year growth

-25%

2 year growth

-16%
Locations
San Mateo, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
CategoriesNew
Product
Requirements
  • Demonstrated success in product management or related experience at fast-growing companies
  • Experience developing complex, innovative technology solutions that scale for millions of users
  • Proven ability to work cross-functionally and with multiple stakeholders to quickly deliver solutions that create value for your users
  • Ability to define and validate hypotheses quickly with qualitative and quantitative data
  • Eligibility to work in the United States
Responsibilities
  • Drive the vision, product strategy, and execution of Slickdeals’ Content & Distribution technology platform, including our product catalog, ingestion pipelines, and recommendation engine
  • Measure and improve deal relevance within Slickdeals’ search and discovery experiences
  • Deliver innovative machine-learning solutions that directly impact Slickdeals’ company goals and set the industry standard
  • Collaborate with other cross-functional leaders and product teams to align the company on our roadmap and resolve dependencies
Desired Qualifications
  • Experience with ML recommendation systems preferred but not required