Data Analyst

About the Role: Data Analyst at Talent Bridge

Talent Bridge is seeking a detail-oriented Data Analyst to support large-scale data curation and evaluation initiatives for advanced generative AI systems. This pivotal role focuses on improving model quality across key dimensions such as visual fidelity, prompt adherence, identity preservation, naturalness, and text generation within images.

You will work closely with engineers and research teams, managing data labeling workflows, maintaining high-volume data pipelines, auditing annotations, and analyzing model outputs to identify quality gaps. This is an onsite role requiring hands-on collaboration with technical teams in Menlo Park, CA.

Key Responsibilities

Data Curation & Labeling Operations

• Manage end-to-end data labeling workflows.
• Enqueue datasets for labeling and maintain labeling interfaces.
• Extract structured labels for modeling teams.
• Manually annotate training data when required.
• Audit and correct human-labeled data.

Data Engineering & Pipelines

• Maintain and optimize large-scale data processing pipelines (billions of images).
• Support data sourcing and content understanding using ML models.
• Leverage LLMs to clean, annotate, and evaluate data.
• Assist in building efficient ETL workflows.

Data Governance

• Maintain dataset portfolio with proper access controls.
• Ensure compliance with data retention and privacy standards.
• Support governance and documentation practices.

Analysis & Model Evaluation

• Identify model quality gaps using structured evaluation protocols.
• Collaborate with engineers to summarize findings and recommend improvements.
• Mine and prepare new datasets for iterative model training.
• Scale validated evaluation frameworks across product teams.

Required Qualifications

• Associate’s degree or equivalent training in Computer Science, Engineering, Physics, Bioinformatics, or other STEM field.
• Basic knowledge of Python and SQL.
• Foundational understanding of computer vision and generative AI models.
• Experience with data ETL workflows or pipelines.
• Familiarity using LLMs for data labeling or evaluation tasks.
• Strong attention to detail and analytical thinking.

Preferred Qualifications

• Prior industry experience in software development, QA, or research.
• Exposure to human-computer interaction or ML evaluation work.
• Experience working in large-scale technology environments.
• Strong written and verbal communication skills.

Work Environment

• Onsite collaboration with engineering teams in Menlo Park, CA.
• Fast-paced, research-driven environment.
• High-impact role supporting next-generation AI systems.

Key skills/competency

• Data Curation
• Generative AI
• Machine Learning
• Python
• SQL
• ETL Workflows
• Data Labeling
• Model Evaluation
• Computer Vision
• Large Language Models (LLMs)