Senior Product Manager (Experimentation & Optimization)

TL;DR

Senior Product Manager (Experimentation & Optimization): Shaping how experimentation drives product decisions across large-scale digital platforms with an accent on statistical validity and measurable business outcomes. Focus on owning the end-to-end experimentation strategy, designing complex A/B and multivariate tests, and translating experimental data into clear product direction.

Location: Must be based in the United States

What you will do

• Define, lead, and refine the enterprise experimentation strategy across digital products and platforms.
• Build and manage experimentation roadmaps aligned with product, customer, and business objectives.
• Design and execute A/B, multivariate, holdout, and sequential tests to validate hypotheses.
• Establish scalable experimentation frameworks, governance models, and best practices.
• Perform deep analysis of experiment outcomes to provide actionable product recommendations.
• Partner with Engineering, Data Science, AI/ML, UX, and Analytics teams to implement and evaluate experiments.

Requirements

• Bachelor’s degree in Business, Computer Science, Engineering, Data Science, or a related field.
• 5+ years of Product Management experience focused on experimentation and data-driven development.
• Hands-on experience with platforms such as Optimizely, Adobe Target, Statsig, or similar tools.
• Strong grasp of statistical principles, including significance testing and sample size estimation.
• Proven ability to analyze complex datasets and translate findings into strategic decisions.
• Must be based in the United States.

Nice to have

• Master’s degree in a relevant field.
• Experience working with large-scale digital platforms, eCommerce, or SaaS organizations.

Culture & Benefits

• Competitive compensation package aligned with market standards.
• Fully remote work flexibility within the US.
• Opportunity to lead experimentation strategy at an enterprise scale.
• Exposure to advanced analytics, AI/ML, and modern product experimentation ecosystems.
• Collaborative, cross-functional environment with a focus on innovation and growth.

Hiring process

• AI-powered matching process to shortlist candidates based on core requirements.
• Final decision and interviews managed by the internal team of the partner company.