Treasury Product Manager II at Bank of America focused on U.S. Real - Time Payments and enhancing client experience. Analyze market trends and manage product risk while collaborating with cross - functional teams.
About the role
- Product Manager leading data platform, ML, and AI strategy at Plaid. Creating foundational systems for data-driven products and collaborating across engineering and data science teams.
Responsibilities
- Define and drive the vision, strategy, and roadmap for Plaid’s data, ML, and AI platforms. Enable teams to move from raw data to insight and intelligence quickly and safely.
- Build and scale foundational systems and tools that power model training, data pipelines, and data-driven products across Plaid.
- Lead initiatives to improve data governance, discoverability, and quality. Ensure secure, compliant, and auditable access to trusted data and models.
- Partner with engineering, data science, and product teams to design scalable online and offline data flows that connect upstream generation with downstream analytics and products.
- Align teams across the Data Org, ML engineering, and product lines such as Credit, Fraud, and Identity. Translate platform investments into measurable impact.
- Stay current on trends in ML, AI, and data infrastructure. Help shape how Plaid applies these technologies responsibly and effectively.
Requirements
- 8+ years of product management experience in data platforms, ML/AI tooling, or developer infrastructure
- Strong understanding of the data and model lifecycle, including collection, governance, training, deployment, and observability
- Experience shipping high-leverage platform products used by data scientists, engineers, or product teams
- Ability to combine strategic thinking with hands-on execution and influence across a wide range of stakeholders
- Builder mindset with comfort in ambiguity and a track record of taking ideas from concept to launch
- [Nice to Have] Experience in regulated or compliance-heavy environments such as fintech or healthcare
- [Nice to Have] Familiarity with modern data stack tools like dbt, Airflow, Feast, MLflow, or Snowflake
- [Nice to Have] Experience shaping data governance, experimentation, or ML practices at scale
Benefits
- medical
- dental
- vision
- 401(k)
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