AI Business Data Analyst
Job in
Torrance, Los Angeles County, California, 90501, USA
Listed on 2026-06-10
Listing for:
UNICON International, Inc.
Part Time
position Listed on 2026-06-10
Job specializations:
-
IT/Tech
Data Analyst, Data Science Manager, AI Engineer (Applied/Software), Data Scientist
Job Description & How to Apply Below
AI Business Data Analyst
Location:
Torrance, CA
Work Model: Hybrid
Compensation: $103-108k
Job Title:
AI Business Data Analyst
Reports To:
CX AI Product Owner
Division: CX & UX Design Division
Department: CX Product
3rd Party Suppliers:
Not accepting 3rd party suppliers for this role
Work Type:
Remote (Onsite 2 days a week)
Travel: 5%
Overtime:
Yes
POSITION OVERVIEW
The AI Business Data Analyst will support American client Motor s Customer Experience digital transformation by providing day-to-day analytics, quality monitoring, KPI definition, evaluation, and insight generation for production generative AI and conversational AI applications.
This role will help ensure AI-powered customer experiences are accurate, reliable, measurable, and continuously improving. The analyst will monitor production LLM application performance, evaluate response quality, build dashboards, identify risks and opportunities, and synthesize insights that inform product roadmap decisions, feature requirements, backlog prioritization, and operational improvements.
The ideal candidate combines strong analytical skills, product sense, technical curiosity, and practical understanding of generative AI applications, including conversational AI, RAG, prompt-based systems, AI evaluation metrics, and LLM-as-a-judge methodologies.
WHAT YOU WILL BE DOING
AI Product Performance, Evaluation & Insights 50%
Establish, monitor, and report on KPIs related to AI product performance, customer experience, user behavior, operational efficiency, and business value.
Analyze production AI application data, including conversation logs, usage patterns, customer feedback, quality signals, escalation trends, and operational telemetry.
Identify issues and opportunities related to response quality, accuracy, hallucination risk, retrieval relevance, content drift, deflection, satisfaction, coverage, and task completion.
Design and support AI evaluation processes, including response quality reviews, evaluation rubrics, benchmark test sets, human-in-the-loop review, and LLM-as-a-judge approaches.
Build dashboards, scorecards, and recurring business reviews that communicate AI application health, trends, risks, and improvement opportunities.
Translate findings into actionable recommendations, product requirements, backlog items, acceptance criteria, and release validation plans.
Product Analytics, Discovery & Roadmap Support 25%
Conduct exploratory analysis to understand user behavior, customer intent, conversation topics, feature usage, and AI-assisted customer journeys.
Identify friction points, emerging needs, product gaps, and opportunities to improve AI-powered customer experiences.
Partner with Product Managers and CX stakeholders to translate data-driven insights into roadmap recommendations, feature concepts, and experimentation priorities.
Support product discovery through analysis of customer feedback, behavioral data, qualitative research, competitive trends, and emerging AI capabilities.
Design and evaluate experiments or A/B tests related to prompts, workflows, retrieval strategies, response patterns, and feature changes.
Agile Product Delivery & Cross-Functional Partnership 25%
Lead or participate in the gathering, analysis, and documentation of business requirements, user stories, acceptance criteria, use cases, process flows, and technical dependencies for AI product enhancements.
Participate in Agile ceremonies including backlog refinement, sprint planning, daily syncs, demos, sprint reviews, and retrospectives.
Support UAT, release validation, and post-release monitoring for prompt updates, indexed content changes, retrieval logic changes, model updates, workflow enhancements, and dashboard/reporting releases.
Partner with Product Owners, AI engineers, data teams, QA, CX stakeholders, vendors, and business leaders to ensure AI products meet customer, operational, and business requirements.
Translate technical AI behavior and data findings into clear business implications for technical and non-technical stakeholders.
Support change management, user support, training materials, and stakeholder communications related to AI product performance and enhancements.
W…
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