Job Description:

Essential Responsibilities:

Inputs to product strategy with cross-functional stakeholders consistent with the shared vision for the product.
Implements the architectural roadmap that balances innovative design and technical implementation, while balancing regulatory requirements, time-to-market, meeting customer needs and product profitability.
Controls for the customer experience and customer needs in product requirements and as an input to decision making.
Monitors metrics that inform the success of products including usability studies, research and market analysis.
Manages one or more workstreams to include analytics, customer discovery, market research and competitive analysis to drive data-driven decision-making.
Monitors product profitability measures, including budget.
Participates in operational mechanisms that drive execution and accountability including Product Reviews, Operating Reviews, and Business Reviews. Interfaces with product leadership as needed.
Partners with content developers, data scientists, product designers and user experience researchers.

Minimum Qualifications:

Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience.

Preferred Qualification:

Experience: 7+ years of product management experience, with 4+ years specifically in platform/infrastructure products or AI/ML domains
Education: Bachelor's degree in Engineering, Computer Science, Data Science, or related technical field; MBA or advanced degree preferred
Technical Background: Strong understanding of machine learning concepts, data pipelines, cloud infrastructure (AWS/GCP/Azure), and software development practices
Platform Experience: Proven track record building and scaling developer platforms, APIs, or internal tooling with measurable adoption
Leadership: Experience leading cross-functional teams and driving consensus among diverse stakeholders
Analytics: Proficiency with data analysis tools and experience making data-driven product decisions
Communication: Excellent written and verbal communication skills with ability to present to technical and non-technical audiences

Technical Skills

Programming: Familiarity with Python, SQL, and API development
ML Tools: Knowledge of model training frameworks, feature stores, and ML monitoring tools
Data Infrastructure: Understanding of data warehousing, real-time streaming, and distributed computing
DevOps: Experience with CI/CD pipelines, infrastructure as code, and automated testing
Security: Knowledge of data privacy, model security, and AI governance frameworks

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