2023 Schedule

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Tuesday, Sep 19
11:00am — 11:30am
Product Track- CBRE
399 attending

Decoding ML/AI: A Practical Guide to Drive Growth & Innovation

Data-Driven Startup Success: Mastering ML/AI for Growth and Innovation

Join us for an immersive session that demystifies the ML world and discover how to confidently navigate the ML/AI journey. Gain priceless insights into aligning objectives, defining metrics, leveraging data science effectively, and making the right trade-offs on the platform side. Leave equipped with practical strategies, tools, and a deep understanding of how ML/AI can propel your startup to new heights. Don't miss this opportunity to unlock your startup's potential and shape a brighter future!

Argie Angeleas is a Group Product Manager at ibotta. He streamlined ML processes, reduced costs, and drove revenue growth through A/B testing and fraud detection. As Director of Product at iReportSource, he implemented ML-based safety scoring and achieved impressive revenue growth. With a Ph.D. in Computer Science, his expertise lies in AI, computer vision, and product management. Argie's exceptional leadership and technical skills have consistently delivered innovation and success in ML, data analytics, and product development.

Matt Reynolds is currently a Principal Platform Engineer on Ibotta's Machine Learning team after stints in DevOps and Architecture. He has had a long and varied career in software development, working on projects as diverse as embedded safety critical software for subway trains, air traffic control systems, and various aspects of eCommerce. Matt has spoken on Microservices, DevOps, and MLOps at meetups and DevOps Days conferences.

Taylor Names is a Principal Machine Learning Engineer at Ibotta and has been a leader and practitioner in Machine Learning and Data Science for the past 7+ years. He has specialized in each phase of the machine learning lifecycle, from product ideation to production deployment with local startups in climate, IoT, and e-commerce spaces. Taylor is passionate about driving important business outcomes by delivering performant, cost-effective, and maintainable machine learning solutions.

Taylor Names
Matt Reynolds
Argie Angeleas