Senior Product Manager – Experimentation & Optimization

US Posted Jun 30, 2026 0 views

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Job description

Team: Product

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Product Manager – Experimentation & Optimization based in the United States.

This is a high-impact product leadership role focused on shaping how experimentation drives product decisions across large-scale digital platforms. You will own the end-to-end experimentation strategy, ensuring product development is grounded in rigorous testing, statistical validity, and measurable business outcomes. Working in a data-rich, cross-functional environment, you will partner closely with engineering, data science, analytics, UX, and AI/ML teams to design and scale experimentation frameworks. The role requires a strong blend of strategic thinking and hands-on execution, translating complex experimental data into clear product direction. You will champion a culture of continuous optimization, enabling teams to make faster, evidence-based decisions. This is an opportunity to influence product strategy at scale while building best-in-class experimentation practices across the organization.

Accountabilities:

  • Define, lead, and continuously refine the enterprise experimentation strategy across digital products and platforms.
  • Build and manage experimentation roadmaps aligned with product, customer, and business objectives.
  • Design, execute, and analyze experiments (A/B, multivariate, holdout, sequential testing) to validate hypotheses and improve user experience.
  • Establish scalable experimentation frameworks, governance models, and best practices across multiple product teams.
  • Perform deep analysis of experiment outcomes, translating data insights into actionable product recommendations.
  • Partner with Engineering, Data Science, AI/ML, UX, Analytics, and Product teams to design, implement, and evaluate experiments.
  • Ensure statistical rigor in experimentation design, including significance testing, sample sizing, and bias evaluation.
  • Communicate experiment results and insights to stakeholders, influencing product strategy and prioritization decisions.
  • Drive a culture of experimentation, continuous learning, and data-driven decision-making across the organization.

  • Requirements:

    • Bachelor’s degree in Business, Computer Science, Engineering, Data Science, or a related field (Master’s preferred).
    • 5+ years of Product Management experience with a strong focus on experimentation, optimization, and data-driven product development.
    • Hands-on experience with experimentation platforms such as Optimizely, Adobe Target, Statsig, or equivalent tools.
    • Strong understanding of experimentation methodologies, including A/B testing, multivariate testing, holdout testing, and sequential testing.
    • Solid grasp of statistical principles such as significance testing, sample size estimation, and bias/variance trade-offs.
    • Proven ability to analyze complex datasets and translate findings into clear, strategic product decisions.
    • Experience building and scaling experimentation programs, frameworks, and governance processes in large organizations.
    • Strong communication, storytelling, and stakeholder management skills across technical and non-technical audiences.
    • Experience working in Agile product environments with cross-functional teams.
    • Preferred experience in large-scale digital platforms, eCommerce, SaaS, or high-growth technology organizations.

    • Benefits:

      • Competitive compensation package aligned with experience and market standards.
      • Fully remote work flexibility within the United States.
      • Opportunity to lead experimentation strategy at enterprise scale.
      • Exposure to advanced analytics, AI/ML, and modern product experimentation ecosystems.
      • Collaborative, cross-functional environment with high-impact product teams.
      • Strong focus on professional growth, innovation, and continuous learning.
      • Opportunity to shape data-driven product culture and decision-making frameworks.

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