Senior Product Manager
Data Infrastructure and ML
Confirmed live in the last 24 hours
Locations
Washington, DC, USA • Remote in USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Data Science
Quality Assurance (QA)
Requirements
- 5+ years of technical product management experience
- Knowledge of systems development, including system integrations, data pipelines, design and testing techniques
- Experience building consensus and accomplishing goals with highly technical stakeholders/partners
- Experience building AI/ML or AI-driven evaluation or recommendation platforms and/or data products with an ability to drive product roadmaps, development, and launch
Responsibilities
- Lead Product Definition: Own and drive multi-year strategy/long-term goals for Risk's data pipeline and ML ecosystem in partnership with Risk Product teams, Engineering, Machine Learning, Data Science, and Policy functions and partner teams across Square
- Define Product Vision: Including all aspects of the roadmap, investment, innovation and experimentation
- Engage Customers: Build and manage the customer pipeline. Proactively identify and address customer pain points to increase adoption. Learn from customers to define the product vision and roadmap
- Execution of Product Planning and Development: Including customer goals and business requirements for product release, ensuring implementation is aligned with product goals and requirements, and ownership of product positioning
- Partner with Data Scientists and Machine Learning Engineers: to deliver technical projects while working across teams to bring new value to Square internal teams
- Meet the Risk platform objectives: by representing your sprint team, their objectives, and strategy with cross-functional stakeholders, Risk leadership, and senior company leaders
- Lead interaction with Engineering teams: Including helping the technical team make tradeoffs based on customer requirements, QA/testing of the product
- Influence senior leaders: Communicate Risk Infrastructure and ML Services vision, strategy, goals, status, and business impact