Product Marketing Manager

The role

You will own positioning, messaging, product launches, and competitive insights. You will work cross-functionally to tell the story of how Uncountable delivers value to R&D organizations.

What you will do

• Craft messaging and positioning for core platform and product modules
• Support demand and lead generation efforts through content and campaigns
• Lead strategy and execution of net new lead generation and lifecycle marketing
• Lead product launches and spotlights across web, email, and sales decks
• Support go-to-market strategy including internal enablement and external rollouts
• Build and maintain customer personas and use case maps
• Develop sales and customer-facing content like battlecards and one-pagers
• Drive competitive intelligence and win/loss analysis
• Partner with Sales and Revenue teams to train reps on value propositions
• Create product-focused assets including videos, decks, and comparison charts

Required qualifications

• Bachelor's degree in Marketing, Communications, or a related field
• 3- 6+ years of experience in product marketing, ideally in B2B SaaS or enterprise technology
• Proven ability to position technical products for business outcomes
• Proven ability to strategize and execute on product marketing efforts
• Experience building and executing lead generation campaigns
• Experience with content creation
• Excellent storytelling, writing, and presentation skills
• Comfort with ambiguity and a startup mindset
• Strong project management skills

Nice to have

• Experience working with (or marketing to) R&D, manufacturing, or industrial audiences
• Marketing/Sales Platform experience: HubSpot, Outreach.io, Salesforce CRM, SEMRush
• Google Analytics
• Experience with graphic design & video editing tools
• Passion for science, chemistry, and/or artificial intelligence
• An aptitude for statistics, mathematics

About the company

Uncountable is an innovative B2B SaaS company providing an AI-driven Laboratory Informatics platform for R&D organizations. They help scientists maximize utilization of experimental data and optimize formulations.