Staff Product Manager, Pricing
New
J
JobgetherInsurtech pricing
Work remotely from anywhere in the United StatesFull-TimeStaff
Salary$168,300–$210,980 per year
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Job Details
- Experience
- At least 8 years of product management experience
- Required Skills
- Product ManagementRESTful APIsLLM
Requirements
- At least 8 years of product management experience, ideally in fintech, insurtech, or another data-intensive and regulated industry.
- Strong systems-thinking skills and familiarity with predictive modeling, APIs, and workflow orchestration.
- Experience collaborating with data scientists, analytics specialists, engineers, or machine learning teams to develop data-driven products.
- Ability to identify opportunities to integrate large language models and advanced AI into data science workflows.
- Strong analytical and data-driven decision-making skills, including translating technical concepts into intuitive product experiences.
- Experience with agile product development and end-to-end product lifecycle management.
- Ability to align cross-functional teams and influence stakeholders without direct authority.
- Willingness and ability to travel approximately 10% of the time, including quarterly in-person team events.
- Preferred: experience as a data scientist, analyst, or Product Manager working closely with data science and machine learning engineering teams.
- Preferred: insurtech experience, particularly in risk assessment, insurance pricing, or related pricing ecosystems.
Responsibilities
- Own and refine the pricing platform roadmap, product vision, and strategic priorities.
- Translate business objectives and technical needs into product strategies, requirements, and execution plans.
- Lead engineers through product discovery, implementation, launch, and continuous improvement.
- Partner with Engineering, Data Science, and Actuarial teams to identify platform needs and prioritize investments.
- Develop product requirements documents that align business strategy with engineering execution.
- Drive machine learning platform capabilities spanning experimentation, training, validation, deployment, and monitoring.
- Explore and integrate AI and large language model technologies into data science and production workflows.
- Develop self-service tools for faster experimentation, feature creation, and model iteration.
- Improve reliability, observability, usability, and consistency between research and production environments.
- Reduce operational and regulatory bottlenecks and build scalable infrastructure for new markets.
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