Product Manager, Contributor (CB) Pay & Incentives

Scale AI • Full-time • San Francisco, California, United States • 3w ago

About the Role:

Scale operates a global marketplace for talent, working with Contributors in over 100 countries.
Understand the cost efficiency and quality for different payment structures - pay by hour, pay by task, etc. to ensure pay transparency, fairness and predictability
This is a highly cross functional role that will involve working with:
- Dedicated Eng, design and data science staffing + PMs across the org
- Growth, Payment operations and delivery operations for each new project launched
- Support for issues that come up

You will:

Understand our business, customer experience and ecosystem position
Set the product strategy for the Pay team
Develop and execute a data-driven, contributor-focused product roadmap through close collaboration with senior leadership, Operations, Data Science, Analytics, Design, and Engineering while balancing business needs.
Translate customer and internal-user needs into clear, well-defined functional and technical requirements backed by data analysis and deep understanding of our users
Guide and interface closely with data analysts and engineering teams to define scope, review and refine technical capabilities, prioritize projects for release, and define new opportunities.
Build long-term instrumentation, monitoring, and evaluation capabilities for product performance, tracking, and to create product insights.
Establish business cases and projected return on investment to identify and prioritize opportunities
Partner with Finance and Business Leaders to manage the impact on the profitability of the overall business.

Ideally, you’d have:

5-8 years of experience in Product Management in the tech industry
Excellent communication and stakeholder management skills, capable of influencing across technical and non-technical audiences to drive strategic outcomes.
Strong business acumen and analytical experience, with demonstrated success in defining emerging or ambiguous user behaviors and driving continuous iteration in high-uncertainty environments.
Nice-to-have:
- Strong understanding of the AI market and willingness to stay at the cutting edge. Deep understanding of modelling workflows, including data labeling, model training, inference, and deployment, with the ability to translate technical concepts into actionable product strategies.
- Experience building products from the ground up, seeing them through the scaling journey
- Experienced in building scalable decision systems, partnering cross-functionally with policy,
Bachelor’s or advanced degree in a quantitative, engineering, or related discipline, with strong comfort in engaging deeply with technical and data-driven problem spaces.

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