Data Product Manager with AI

C2C
  • You translate strategy into a clear product roadmap, prioritizing data and AI capabilities that deliver measurable impact for users and the business.
  • You have led the design and operationalization of solutions focused on data quality, metadata management, governance, lineage, taxonomy, and AI readiness (feature stores, training data quality, and model inputs).
  • You manage the end‑to‑end Institutional Client product development lifecycle, delivering data and AI‑enabled features iteratively to solve real business problems.
  • You partner closely with the Institutional Data Science and Engineering teams to enable AI/ML use‑cases such as advanced analytics, personalization, predictive modeling, and intelligent automation.
  • You establish strong partnerships with business and technology stakeholders, creating continuous feedback loops to refine product value and adoption.
  • You develop a deep understanding of upstream and downstream systems to shape data models, APIs, and AI consumption patterns.
  • You ensure thoughtful product evolution, addressing product lifecycle management, adoption and migration experiences, and clear enablement for users.
  • You drive product discovery, requirements definition, and feature prioritization using modern product and agile best practices, informed by data and user insights.

What We’re Looking For

  • 5+ years of Product Management or Data Management experience, with a proven track record of launching and scaling data platforms and/or AI‑enabled products.
  • Bachelor’s degree; Nice to Have: Bachelor’s degree in in Statistics, Mathematics, Computer Science, Engineering, or a related field; Master’s degree preferred.
  • Experience managing B2B or B2B2C data and AI products throughout the full product lifecycle, ideally within Financial Services, Asset Management, or another highly regulated industry.
  • Hands‑on experience working with data platforms, analytics tools, and AI/ML ecosystems (e.g., data warehouses/lakes, feature stores, model pipelines, MLOps concepts).
  • Ability to perform and interpret data analysis and profiling using SQL; Nice to Have: Python, and/or data visualization tools to inform product decisions.
  • Strong ability to prioritize and communicate product roadmaps across diverse business functions and geographies.
  • Comfort operating in ambiguity, with the ability to adapt product strategy as AI capabilities, business needs, and partner priorities evolve.
  • Exceptional written and verbal communication skills, with the ability to influence audiences ranging from senior leaders to engineers and data scientists.

High curiosity and a desire to deeply understand and simplify complex data and AI domains.

  • Proficiency in applying both qualitative and quantitative methods to define, measure, and continuously improve product success.
  • Entrepreneurial mindset with a bias for action—comfortable rolling up your sleeves and turning incomplete or conflicting inputs into clear execution plans.
  • A high bar for product excellence, with strong attention to detail and a focus on delivering reliable, scalable, and trustworthy data and AI products.
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