Connor Davis
Kansas City, Missouri,United States
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Connor Davis is a results-driven Senior Product Manager with 10 years of experience in the tech industry, specializing in SaaS product development, user experience design, and market strategy. He has a proven track record of launching successful products, driving user adoption, and leading cross-functional teams in fast-paced, agile environments. Connor is passionate about leveraging data analytics and user feedback to build innovative solutions that solve real-world problems and deliver exceptional value. He is adept at translating complex technical concepts into clear, actionable product roadmaps and excels at stakeholder management and communication.
Professional Summary
Connor Davis's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Notable Achievements
Launched 'InsightFlow' SaaS Platform
Led the end-to-end product lifecycle for 'InsightFlow,' a B2B analytics platform, from initial concept through market launch. Achieved 10,000+ active users and $1.5M ARR within the first 12 months.
Mobile App User Engagement Growth
Redesigned the user onboarding experience for a flagship mobile application, resulting in a 40% increase in user retention and a 25% uplift in daily active users within six months.
Product Team Expansion and Mentorship
Successfully scaled the product management team from 3 to 8 members, implementing new agile processes and mentoring junior product managers, significantly improving team velocity and output quality.
Strategic Partnership Development
Identified and secured three key strategic partnerships with complementary technology providers, expanding market reach and adding significant value to the core product offering.
Educational Background
Bachelor of Science - BS, Computer Science
Kansas State University - Year 2018
Technology Solutions
Northland Center for Advanced Professional Studies (CAPS) - Year 2017
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Company Overview
Union LabsUnion AI is the company spearheading the development of Flyte, an open-source, Kubernetes-native workflow orchestration platform designed for complex data and machine learning pipelines. They focus on simplifying MLOps and enabling scalable, reproducible, and maintainable AI/ML applications for data scientists and ML engineers.
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