Staff Product Manager, Pricing

Jobgether

United States

Remote

USD 168,000 - 211,000

Full time

3 days ago
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Benefits offered by this job

Remote work flexibility
Equity offering
Bonus eligibility
HQ Columbus, OH—optional travel for in

Job summary

Jobgether is seeking a Staff Product Manager, Pricing in the United States to define vision, strategy, and a roadmap for pricing platforms and ML-driven pricing Systems. You will collaborate with Engineering, Data Science, and Actuarial teams to accelerate experimentation and production deployment while ensuring regulatory readiness.

The role emphasizes cross-functional leadership, data-driven decision making, and the integration of AI/LLM capabilities to streamline research and deployment.

Qualifications

  • At least 8 years of product management experience in data-intensive and regulated environments.
  • Proficiency with predictive modeling, APIs, and workflow orchestration.

Responsibilities

  • Define pricing platform vision and roadmap for 2027 and beyond.
  • Lead engineers through the full product lifecycle from discovery to production.
  • Develop PRDs aligning business strategy with engineering execution.
  • Build scalable pricing infrastructure and observability across workflows.
  • Explore AI/LLM opportunities to enhance data science workflows.

Skills

Product management
Data science collaboration
AI/ML integration
Agile methodologies
Stakeholder management

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Product Manager, Pricing based in the United States.

We are seeking an experienced Staff Product Manager to define the vision, strategy, and roadmap for the technology platforms that power advanced pricing capabilities in a data-driven, regulated environment. In this strategic and highly cross-functional role, you will lead the evolution of pricing infrastructure, internal tools, and machine learning systems that turn research and data into production-ready pricing decisions. Working closely with Engineering, Data Science, and Actuarial teams, you will accelerate experimentation, improve model deployment, and strengthen the reliability and observability of pricing workflows. You will also explore how emerging AI and large language model technologies can streamline research, validation, and production processes. This is an opportunity to influence a critical business capability, lead complex product initiatives, and build scalable systems that support growth across diverse regulatory markets. The position offers flexibility to work remotely from anywhere in the United States, with occasional travel for team collaboration.

Accountabilities
  • Product Vision and Strategy
    • Own the pricing platform roadmap, continuously refining the product vision and strategic priorities for 2027 and beyond.
    • Define product opportunities that strengthen pricing capabilities, accelerate decision-making, and support long-term business growth.
    • Translate business objectives and technical needs into clear product strategies, requirements, and execution plans.
    • Maintain a prioritized product backlog using structured product management frameworks and data-driven decision-making.
  • Cross-Functional Leadership
    • Lead engineers through the full product lifecycle, from ideation and discovery to implementation, launch, and continuous improvement.
    • Partner with Engineering, Data Science, and Actuarial teams to identify platform needs and prioritize investments.
    • Develop clear product requirements documents (PRDs) that align business strategy with engineering execution.
    • Build alignment across stakeholders, influence decisions without direct authority, and ensure teams remain focused on high-impact outcomes.
  • Machine Learning Platform Development
    • Drive the development of end-to-end machine learning platform capabilities that help researchers move efficiently from experimentation to production.
    • Improve workflows across data readiness, feature pipelines and feature stores, model training and orchestration, model registries and versioning, automated validation, model serving, diagnostics, and monitoring.
    • Explore and integrate emerging AI and large language model technologies to automate and improve data science, research, modeling, testing, validation, and deployment workflows.
    • Develop self-service tools that enable faster experimentation, feature creation, and model iteration.
    • Improve consistency between research and production environments while increasing workflow reliability, observability, usability, and speed.
  • Operational Efficiency and Regulatory Readiness
    • Accelerate the transition from new data and model features to production deployment.
    • Reduce operational friction and regulatory bottlenecks across pricing and filing workflows.
    • Ensure pricing platform capabilities can adapt to state-specific regulatory and operational requirements.
    • Support nationwide expansion by building scalable infrastructure and processes that accommodate new markets.
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 technical concepts such as 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 for integrating large language models and advanced AI capabilities into everyday data science workflows.
  • Strong analytical and data-driven decision-making skills, with the ability to translate complex technical concepts into intuitive product experiences.
  • Excellent communication and stakeholder management skills, including the ability to align cross-functional teams around shared priorities.
  • Experience with agile product development methodologies and end-to-end product lifecycle management.
  • Customer-centric mindset and a demonstrated ability to improve user experiences and product usability.
  • Strong organizational skills, attention to detail, and the ability to manage competing priorities in a dynamic environment.
  • Adaptability and comfort navigating evolving scope, ambiguity, and changing business needs within a growing organization.
  • Collaborative leadership style and the ability to influence stakeholders without relying on direct authority.
  • A hands‑on, results‑oriented approach with the initiative to solve problems and drive execution in a fast‑paced environment.
  • Willingness and ability to travel approximately 10% of the time, including quarterly in-person team events.
Preferred Qualifications
  • Previous experience as a data scientist, analyst, or Product Manager working closely with data science and machine learning engineering teams.
  • Experience in insurtech, particularly within risk assessment, insurance pricing, or related pricing ecosystems.
Benefits
  • Salary: $168,300–$210,980 per year.
  • Eligibility for a competitive bonus.
  • Equity offering.
  • Remote work flexibility: Work from a location of your choice within the United States.
  • Flexible approach to where work is performed, with an established headquarters in Columbus, Ohio.
  • Opportunities to lead high-impact product initiatives at the intersection of pricing, machine learning, and advanced AI technologies.
  • Approximately 10% travel, including quarterly in-person team events.
Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

We appreciate your interest and wish you the best!

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