Senior Technical Product Manager

The Zebra•Austin, TX

1d•$130,000 - $180,000•Hybrid

About The Position

The Product Team at The Zebra is expanding, and we are seeking a Senior Technical Product Manager to support the company's growing needs. This role's mission is to transform cutting-edge models into seamless customer experiences. The Senior Technical Product Manager will lead the full model lifecycle, from creative feature engineering to rigorous production monitoring and drift management. This is a hands-on leadership role for someone who thrives on the technical challenge of keeping AI performing at its peak in a live environment. The position reports directly to the Director of Product, and will work closely with the Chief AI Officer, the data science team, and engineering to achieve company and AI Village goals.

Requirements

3+ years experience in a consumer-facing product management or equivalent role
Experience working closely with engineers and designers in agile or scrum environments.
Strong analytical, problem-solving, and organizational skills.
Excellent written and verbal communication skills, including the ability to translate complex ideas for different audiences.
Customer-first mindset with a passion for creating intuitive, impactful products.
Proficiency in product tools like Jira, Confluence, Figma, and data tools like Looker, Amplitude, or similar.

Nice To Haves

Experience in insurance/insurtech is a plus
Experience operating in a regulated industry (e.g., financial services, healthcare) is also strongly preferred.

Responsibilities

Define and own the product vision, strategy, and roadmap for data science and machine learning initiatives
Translate business problems into well-scoped data science use cases and product requirements
Partner closely with data scientists, data engineers, and ML engineers to deliver models and data products end to end
Prioritize features, experiments, and model improvements based on impact, feasibility, and risk
Lead discovery efforts to identify opportunities where data science can create meaningful business value
Ensure models are production-ready, monitored, and continuously improved post-launch
Collaborate with engineering and platform teams on data infrastructure, tooling, and scalability
Communicate clearly with stakeholders on trade-offs, timelines, model performance, and outcomes
Define success metrics and evaluate product performance using quantitative and qualitative insights
Ensure responsible use of data, including privacy, fairness, and ethical considerations