Senior Product Manager, OfferFit

• Builder: you love building products that users love and obsess over the tiniest details to deliver a delightful customer experience
• Entrepreneurial: you proactively identify opportunities and risks, work around obstacles, and always seek creative ways to improve processes and outcomes
• Structured and organized: you can structure a plan, align stakeholders, and see it through to execution
• Clear communicator: you are able to express yourself clearly and persuasively, both in writing and verbally
• Must be fluent in English, both written and verbal
• Up to 10-15% travel for company-wide quarterly gatherings, team offsite workshops, customer meetings, and industry-related events

• This is an exciting opportunity to get in on the ground floor building an advanced ML B2B product which addresses a >$10B pain point for lifecycle marketers
• We’re in the early innings here at OfferFit and expect explosive growth in the next few years
• As a Senior Product Manager, you will own product strategy, feature prioritization, roadmap and execution for OfferFit’s AI Decisioning Engine
• In particular, you will:
• Engage with our customers directly to learn and gather feedback
• Develop prioritized feature product roadmaps
• Own cross-functional execution of the roadmap, working with various stakeholders across UI/UX, Frontend and Backend Engineering, Customer Success and Implementation teams
• As one of the first PMs at OfferFit, define the structures and processes to grow and continually improve the Product function
• Work closely with OfferFit’s founders

• Generous PTO policy: Starting at 25 days PTO per year
• 100% remote work environment: With flexible hours
• Quarterly gatherings: Where we meet in person in different cities to work together, bond as a team, and celebrate our progress
• Weekly team events: Lunch and learns, trivia, virtual escape rooms, town halls, and team health "barometer" meetings

Total funding: $39m

In the realm of digital marketing, traditional A/B testing is facing significant challenges in optimizing and personalizing communication strategies. The limitations of this approach, which is employed to measure the effectiveness of different messages among user groups, include scalability issues and the inability to continuously adapt to evolving user behaviors.