Product Manager, Machine Learning - New York, United States - Harnham

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    Description

    Product Manager, Machine Learning

    SaaS

    Remote

    $180k - $200k

    Company Overview:

    My client is a pioneering force in MLOps, and stands as a machine-learning platform of choice for organizations globally, facilitating seamless tracking, comparison, explanation, and optimization of models from training to production.

    Background:

    They are actively seeking a Senior Product Manager with a robust background in data science, emphasizing expertise in MLOps. The ideal candidate should bring over 5 years of product management experience, showcasing a proven track record in delivering exceptional products and a deep understanding of machine learning.

    Key Qualifications:

    • 5+ years of product management experience with a focus on MLOps
    • Proven track record in delivering high-quality products within the MLOps domain
    • Proficiency in collaborating with engineers to shape technical architecture
    • Excellent communication skills for diverse audiences (engineering, marketing, sales, individual users, and B2B customers)
    • Expertise in design and UX with a strong background in data products or working with Machine Learning teams
    • Familiarity with Java, React, Python, AWS, SQL

    Responsibilities:

    • Establishing MLOps-focused product requirements, goals, performance indicators, and milestones
    • Collaborating with cross-functional teams to ensure the successful delivery of MLOps-focused roadmaps
    • Driving MLOps-centric product development in collaboration with top-tier engineering and design teams
    • Analyzing and disseminating user data and feedback across the team to track the MLOps impact
    • Integrating market analysis, research, and usability studies into MLOps-focused product requirements
    • Communicating MLOps-driven product plans, benefits, and results to internal stakeholders
    • Monitoring and measuring MLOps-focused launched products, utilizing insights to shape the MLOps product roadmap.