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Entry Level Artificial Intelligence Cognitive Science Jobs in California

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Infographic showing various Entry Level Artificial Intelligence Cognitive Science job openings in California as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 24% Part Time, and 4% Contract. Highlights an 74% Physical, 3% Hybrid, and 23% Remote job distribution.

Artificial Intelligence

Los Angeles, CA • On-site

BridgeNexus Technologies Inc
IT Services • 11 - 50 employees
Learn more about BridgeNexus Technologies Incexternal

Other

Posted 22 days ago

Job description

Hi, WE have below 2 positions with our direct client and both are hybrid position and kindly reply asap at your interest so I reach you immediately to schedule one round interview with client .
 
JOB 1:  AI Analyst with Healthcare Background
Location: Woodland Hills. CA (Commute three times in a week to Woodland Hills office)
Duration: Long term
Client: Direct client
JOB 2: AI ML Developer with Data Science experience
Location: Woodland Hills. CA (Commute three times in a week to Woodland Hills office)
Duration: Long term
Client: Direct client 
 
 
 
 
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Role
Job Description
1
AI Analyst with Healthcare Background
seeking an experienced Artificial Intelligence & Machine Learning (AI/ML) Systems Analyst to bridge the gap between business stakeholders, data scientists, AI/ML engineers, and technology teams. This role will be responsible for analyzing business problems, defining AI/ML solution requirements, evaluating data readiness, supporting model implementation, and ensuring AI solutions align with business objectives, regulatory requirements, and enterprise governance standards. The ideal candidate will possess strong analytical skills, healthcare domain knowledge, and experience working with AI, machine learning, and Generative AI technologies.
Key Responsibilities
Business & Systems Analysis
  • Collaborate with business stakeholders to identify opportunities for AI/ML-driven process improvements and automation.
  • Elicit, analyze, and document business, functional, and non-functional requirements.
  • Create user stories, process flows, use cases, data mappings, and acceptance criteria.
  • Translate business requirements into AI/ML solution specifications.
  • Support backlog grooming, sprint planning, and Agile delivery processes.
AI/ML Solution Analysis
  • Partner with AI/ML engineers and data scientists to define model objectives and success metrics.
  • Analyze data sources and determine data quality, completeness, and readiness for AI initiatives.
  • Support predictive analytics, recommendation systems, NLP, GenAI, and intelligent automation initiatives.
  • Evaluate AI model outputs and assist with validation, testing, explainability, and business adoption.
Data & Analytics

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