Principal Product Manager - ML / Subscriptions Growth

What You'll Do

• Set the product vision and multi-quarter strategy for ML- and AI-driven subscriber growth across awareness, acquisition, activation, retention, and monetization. These strategies will define and inform how we develop data signal sourcing, data platform capabilities, and model validation.
  
• Own a portfolio of initiatives end-to-end, aligning multiple squads and stakeholders around clear goals, sequencing, and measurable outcomes (conversion, churn, ARPU, LTV).
  
• Turn behavioral and revenue signals into crisp hypotheses, define success metrics and guardrails, and drive an experimentation roadmap that’s prioritized by impact and learning value.
  
• Establish strong measurement practices (A/B testing, incrementality, causal inference where appropriate), and ensure we scale only what demonstrates durable lift against strong baselines.
  
• Set direction to prioritize and develop data signals, attributes, data products, and feature store requirements
• Drive lifecycle and personalization strategies (including trial design, offer targeting, win-back, and plan nudges) that balance user value, revenue outcomes, and long-term trust.
  
• Partner with pricing and packaging stakeholders to design experiments that improve monetization while remaining transparent, locally relevant, and sustainable.
  
• Make pragmatic decisions about when to use ML, GenAI, heuristics, or rules, balancing ROI, complexity, latency, maintainability, and launch risk. Start with simple solutions before investing in complex systems.
  
• Ensure production readiness for ML-backed experiences through monitoring, performance evaluation, guardrails, data quality standards, and rollout plans that work at global scale.
  
• Communicate trade-offs and insights clearly to senior leadership, translating technical complexity into business impact and crisp decisions.
• Elevate product craft across the mission by mentoring other PMs, strengthening decision frameworks, and building a culture of learning, accountability, and inclusive collaboration.

Who You Are

• You bring 8+ years of product management experience, including leading data-driven or ML-backed products from discovery through global rollout.
  
• You have led platform or shared-capability product work where driving alignment and adoption was key to success, not just shipping features
• You have strong technical fluency in experimentation design, A/B testing, causal inference concepts, ML fundamentals, recommender/personalization systems, and data infrastructure (feature stores, attribute systems, data pipelines, data governance)..
  
• You have experience defining and governing shared data products or data layers - establishing standards and processes
• You consistently connect product decisions to measurable business outcomes, with a track record of improving conversion, retention, churn, ARPU, and/or LTV.
  
• You have experience in subscription or e-commerce business models, including lifecycle optimization, offers, pricing, packaging, or marketplace dynamics.
  
• You demonstrate strong judgment in choosing the simplest effective solution, and you know when advanced ML or GenAI is worth the trade-offs. You resist over-engineering and insist on proving incremental value.
  
• You build responsibly, considering fairness, bias mitigation, privacy, and localization — especially when personalization affects pricing, offers, or eligibility.
  
• You lead with clarity and empathy, give and receive feedback well, and raise the bar through coaching and principled decision-making.
• You influence without authority across engineering, data science, design, analytics, finance, and commercial stakeholders, and you’re skilled at aligning teams through ambiguity. You are experienced with resolving trade-offs between competing priorities.
  

Where You'll Be

• This role is based in London, United Kingdom or Stockholm, Sweden.
• We offer you the flexibility to work where you work best! There will be some in-person meetings, but still allows for flexibility to work from home.