6 days ago

Data Analyst I

Nexus Consulting

Remote
Full Time
$170,000
Remote

Job Overview

Job TitleData Analyst I
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$170,000
LocationRemote

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Job Description

About the Role

We are seeking a detail-oriented Data Analyst I to support large-scale data curation and evaluation initiatives for advanced generative AI systems. This 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 to manage data labeling workflows, maintain high-volume data pipelines, audit annotations, and analyze model outputs to identify quality gaps.

This is an onsite role requiring hands-on collaboration with technical teams.

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

Equal Opportunity Statement

We are an equal opportunity employer and consider all qualified applicants without regard to legally protected characteristics. Qualified applicants with arrest and conviction records will be considered in accordance with applicable laws. Reasonable accommodations are available upon request.

Key skills/competency

  • Data Curation
  • Data Labeling
  • Generative AI
  • Model Evaluation
  • Python
  • SQL
  • ETL Workflows
  • Computer Vision
  • LLMs
  • Analytical Thinking

Tags:

Data Analyst I
Data Curation
Data Labeling
Model Evaluation
Data Pipelines
LLM Annotation
AI Systems
Quality Assurance
ETL Workflows
Data Governance
Structured Evaluation
Python
SQL
Generative AI
Computer Vision
Machine Learning
LLMs
Data Processing
Databases
Cloud Platforms

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How to Get Hired at Nexus Consulting

  • Research Nexus Consulting's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume for AI roles: Highlight experience with generative AI, LLMs, data pipelines, and quality assurance.
  • Showcase data analysis expertise: Emphasize Python, SQL, ETL workflows, and model evaluation capabilities.
  • Prepare for technical interviews: Practice problem-solving related to data curation, data quality, and AI model performance.
  • Demonstrate collaborative spirit: Discuss experiences working closely with engineering and research teams on complex projects.

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