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Product Manager (Computer Vision & Data Products)

Zesty.ai

full-remotemidpermanentproduct-management Full remote - Toronto, CA 73 days ago via WTTJ

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Tags

Product ManagementComputer VisionData ProductsMachine LearningLarge Language ModelsSQLPythonRisk ModelingAnalyticsStakeholder Management

About the role

Role overview

Zesty.ai is hiring a Product Manager for Computer Vision & Data Products. You will own the end-to-end product and feature development lifecycle, build roadmaps for analytics and model development, and serve as the model owner / subject matter expert with both customers and regulators.

Key missions

  • Own the product and feature lifecycle from inception through field launch for machine learning, large language models, and computer vision.
  • Build the analytics and model development roadmap for data and risk solutions by researching and analyzing relevant information sources.
  • Partner closely with data scientists and software engineers as a key member of the product development team.
  • Act as model owner and subject matter expert when interfacing with regulators and customers.

Requirements

  • 3–6 years of work experience in analytics, data science, and/or risk/financial/climate modeling (or a relevant quantitative field).
  • 1–2 years of Product Management experience, specifically with data products or model-based features (e.g., actuarial risk, climate risk, credit risk, or search models).
  • Legally eligible to work in Canada.
  • Proficiency in SQL, Excel, and Python.
  • Strong communication skills, including creating executive-style presentations.
  • Comfortable using AI tools to automate and accelerate work (e.g., Claude Cowork).
  • Ability to manage multiple competing priorities and deliver on time.
  • Bachelors or Masters in a quantitative field (Engineering, Sciences, Commerce).

Nice-to-haves

  • Exposure/experience in insurance, real estate, and risk modeling.
  • Experience working with computer vision models.

About Zesty.ai

Zesty.ai is a technology company focused on building data products and applying machine learning—including computer vision and large language models—to deliver analytics and risk-related solutions. The role emphasizes product ownership across model development and deployment, working closely with data scientists and software engineers.

Scraped 5/13/2026