Role description
Job Title: Associate Principal - Data Sciences
Work Location- Irvine, CA
Job Description:
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 prioritization using modern products 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 Statistics, Mathematics, ComputerScience, 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.
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.
