Pearl - Senior Product Manager
Requirements
• Overall professional experience of 5+ years is required • 4+ years of experience in product management across B2B and B2C products. • Possesses hands-on expertise in experimentation methodologies, including A/B testing and multivariate analysis, to drive data-informed decision-making. • Experience syncing up with both Paid and Organic Marketing teams — you know how to speak their language. • Demonstrates a strong ability to identify inefficiencies and proactively implement automation-driven solutions to improve processes and outcomes. • Brings a collaborative mindset with a deep appreciation for partnering with UX and Analytics teams to solve meaningful customer problems. • Exhibits inspiring leadership, effectively aligning and motivating cross-functional teams toward ambitious, high-impact goals. • Leverage generative AI tools to test and optimize ad copy, page messaging, and creative assets, while collaborating closely with engineering teams on AI/ML-powered features to translate insights into effective product decisions. • Our Commitment to an Inclusive Workplace
Responsibilities
• You'll be the go-to person for identifying and solving pain points across our marketing teams and customer journey, and you won't just guess, you'll test it all through A/B experiments like a pro. • Lead the charge with UX, Analytics, and Engineering to turn sprint planning into sprint winning. • Align teams, cut through the noise, and keep everyone rowing in the same direction (yes, you’re that person). • Partner closely with Marketing to ensure product and marketing strategies are best friends, not distant cousins. • Simplify acquisition workflows, build smart tools, and make “efficiency” more than just a buzzword. • Dive deep into the data, spot the growth levers, and bring insights that actually move the needle. • Ideate, pitch, and power growth strategies with real business impact. • AI-Generated Content: Use generative AI tools to test ad copy, page messaging, and creative assets. • AI Collaboration: Work closely with engineering on AI/ML-powered features and translate insights into product decisions.
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