6 days ago

Data Analyst I

Nexus Consulting

Remote
Full Time
$160,000
Remote

Job Overview

Job TitleData Analyst I
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$160,000
LocationRemote

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Job Description

Data Analyst I at Nexus Consulting

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
  • Data Pipelines
  • Model Evaluation
  • Python
  • SQL
  • ETL Workflows
  • LLMs
  • Computer Vision

Tags:

Data Analyst
Data Curation
Data Labeling
Model Evaluation
Data Pipelines
ETL Workflows
Generative AI
Data Quality
Content Understanding
Annotation
Python
SQL
LLMs
Computer Vision
Machine Learning
AI Systems
Datasets
Data Processing
Structured Labels

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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 data roles: Highlight experience in data curation, labeling, Python, SQL, and generative AI.
  • Showcase analytical and problem-solving skills: Be prepared to discuss how you identify and resolve data quality issues.
  • Prepare for technical discussions: Understand data pipelines, ETL workflows, computer vision, and LLM applications.
  • Demonstrate collaboration and communication: Emphasize experience working closely with engineering and research teams.

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