Taxonomy Analyst Jobs in California (NOW HIRING)

Job Summary
We are seeking a Business Systems Analyst / Technical Business Analyst / Data Analyst with strong hands-on SQL coding experience and a solid background working with data platforms, analytics, and AI-enabled solutions. This role focuses on translating business strategy into actionable requirements and roadmaps while supporting data quality, governance, metadata, lineage, data modeling, and AI/ML initiatives. The ideal candidate will bridge business and technical teams and use data-driven insights to support scalable and reliable solutions.
Key Responsibilities
• Translate business strategy into clear product roadmaps, prioritizing data and AI capabilities that deliver measurable business and user impact.
• Perform hands-on SQL coding, data analysis, and data profiling to support business and technical requirements.
• Lead the design and operationalization of solutions focused on data quality, metadata management, governance, lineage, taxonomy, and AI readiness.
• Support AI readiness initiatives involving feature stores, training data quality, and model inputs.
• Manage the end-to-end product development lifecycle for data and AI-enabled capabilities.
• Partner closely with Data Science and Engineering teams to support AI/ML use cases, including advanced analytics, personalization, predictive modeling, and intelligent automation.
• Gather, analyze, document, and translate business requirements into clear functional and technical requirements.
• Develop a strong understanding of upstream and downstream systems to help define data models, APIs, integrations, and AI consumption patterns.
• Build strong partnerships with business and technology stakeholders and establish continuous feedback loops to improve solution value and adoption.
• Support product lifecycle management, adoption, migration, and user enablement activities.
• Drive product discovery, requirements definition, and feature prioritization using Agile and modern product management practices.
• Use qualitative and quantitative methods to define, measure, and continuously improve product and solution performance.
• Analyze complex and potentially conflicting requirements and translate them into clear execution plans.
• Collaborate with stakeholders across business functions and geographies to communicate priorities, roadmaps, dependencies, and expected outcomes.
• Support the delivery of reliable, scalable, governed, and trustworthy data and AI solutions.
Required Qualifications
• 5+ years of experience in Product Management, Data Management, Business Systems Analysis, Technical Business Analysis, Data Analysis, or a related field.
• Strong hands-on SQL coding experience with the ability to perform data analysis and profiling.
• Experience working extensively on the data side with data platforms, data models, analytics, and related technologies.
• Experience launching, supporting, or scaling data platforms and/or AI-enabled products.
• Experience with data quality, metadata management, data governance, lineage, and taxonomy.
• Experience working with data platforms and analytics ecosystems, including data warehouses and data lakes.
• Understanding of AI/ML ecosystems, including feature stores, model pipelines, training data, and MLOps concepts.
• Experience managing or supporting B2B or B2B2C data and AI products throughout the product lifecycle.
• Ability to translate business requirements into actionable functional and technical requirements.
• Strong ability to prioritize and communicate roadmaps across diverse business and technical stakeholders.
• Experience using qualitative and quantitative methods to measure and improve product success.
• Excellent written and verbal communication skills with the ability to collaborate with senior leaders, engineers, data scientists, and business stakeholders.
• Bachelor's degree or equivalent relevant experience.
Preferred Qualifications
• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, or a related field.
• Experience using Python for data analysis.
• Experience with data visualization and analytics tools.
• Experience within Financial Services, Asset Management, or another highly regulated industry.
• Experience supporting advanced analytics, predictive modeling, personalization, or intelligent automation initiatives.