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Salary
≈ $102k – $227k per year (Estimated)
Location
Hybrid (Bnei Brak, Israel)
Seniority
Staff · 8+ years exp

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 12, 2026.

Overview
Company
Impact
Profile match
Viber is a messaging and voice-over-IP application owned by Japan's Rakuten that offers free encrypted chats, voice and video calls, group communities, channels and paid Viber Out calls to regular phone numbers. Founded in 2010, the app has hundreds of millions of users, especially in Eastern Europe, the Middle East and Southeast Asia, and runs development centres in Minsk and other cities. The company is headquartered in Luxembourg City, Luxembourg.

Description

Rakuten Viber is one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and be part of the journey that makes us a super-app. Our mission is to make people’s lives easier by enabling meaningful connections.

Viber Dating mission is to establish a trusted environment for singles to cultivate real human connections with genuine individuals, fostering significant relationships through a best-in-class experience integrated directly within the Viber ecosystem

As a Product Manager for Viber Dating, you will be a driving force of our growth. You will navigate high levels of ambiguity to pioneer a scaling product domain, leveraging Viber’s massive scale.

Responsibilities

  • Drive the Dating Product Strategy (0-to-1 & Scale): Closely impact the multi-year vision, roadmap, and core product surface for Viber Dating. Turn strategic ambiguity into a clear, executable roadmap, making critical tradeoffs to deliver measurable business and user impact.
  • Product Discovery & Innovation: Drive continuous product discovery through wireframes, prototypes, and user research. Navigate how we welcome new users, how we facilitate exploration, how we help people connect authentically
  • Executive Leadership & Cross-Functional Alignment: Act as the domain leader, collaborating with global executive stakeholders, design, engineering, analytics, marketing, and Trust & Safety teams. Bring people along by communicating complex ML logic and product strategy clearly to both technical and non-technical audiences.
  • Data-Driven & Evidence-Based Decisions: Lead a KPI-focused mindset. Use A/B experiments, behavioral data, and qualitative research to guide your decisions when signals are imperfect.
  • From product to revenue: Drive monetization opportunities that are win-win for our customers.
  • Mentorship & Excellence: Raise the bar for the entire product organization. Push your team and peers for excellence by setting a high standard for product craft, documentation, and user-centric thinking.

Requirements

  • Experience: 8+ years of product management experience, with at least 4+ years in a senior/principal capacity. Proven track record in B2C mobile applications at scale.
  • Domain Expertise: Significant experience in B2C, Marketplaces, or other consumer products. You understand the nuances of products that match people or content. Experience in dating solutions is a big advantage but not a must.
  • Leadership in Ambiguity: Exceptional ability to navigate ambiguity, launch 0-to-1 products, and make principled calls in high-impact spaces. You gather people around a goal using interpersonal skills and evidence.
  • Data Storytelling: A masterful storyteller who uses user data and key metrics to explain the narrative, translating complex technical challenges into simple, compelling words.
  • Product skills: you should act as a senior product leader, deeply empathize with the customer problem, bring to the table data-backed insights and hypotheses, and be able to take them to a working MVP that delights our customers.

Advantages

  • Successful experience in user monetization in direct to consumer apps.
  • Curiosity about the psychology of dating, human connection, and the ethics of algorithmic systems.
  • Algo Fluency: Comfort partnering with Data Science, ML, recommendation systems or ranking algorithms.
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