5 days ago

Data Analyst I

North Star Staffing

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

About the Data Analyst I Role

North Star Staffing is seeking a detail-oriented Data Analyst I to support large-scale data curation and evaluation initiatives for advanced generative AI systems. This role is crucial for 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, focusing on managing data labeling workflows, maintaining high-volume data pipelines, auditing annotations, and analyzing model outputs to identify quality gaps.

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
  • Data Labeling
  • ETL Workflows
  • SQL
  • Python
  • Generative AI
  • Computer Vision
  • Machine Learning
  • Data Governance
  • Analytical Thinking

Tags:

Data Analyst
Data Curation
Data Labeling
ETL
SQL
Python
Generative AI
Computer Vision
Machine Learning
Data Governance
Analytical Thinking
Model Evaluation
Data Pipelines
AI Quality
Prompt Adherence
Software Development
Research
QA
Human-Computer Interaction
Large-scale Data

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How to Get Hired at North Star Staffing

  • Research North Star Staffing's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor to align your application.
  • Tailor your resume for Data Analyst I: Highlight experience with data curation, ETL workflows, Python, and SQL, using keywords from the job description.
  • Showcase AI/ML understanding: Emphasize foundational knowledge of generative AI, computer vision, and LLMs in your projects and experience.
  • Prepare for technical assessments: Practice Python scripting, SQL queries, and demonstrate problem-solving skills related to data pipelines and analysis.
  • Articulate analytical thinking: During interviews, provide examples of how you've identified data quality issues and recommended improvements effectively.

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