NASA Qaulity Data Analyst (Customer Onsite)

Benefits

Parental leave

Not verified

Non-birth-parent leave

Not verified

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 7, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source

Seniority

Mid From the posting source

Work mode

Onsite From the posting source

In-office days

5 days From the posting source

Schedule

Shift type

Not verified

Weekend work

Not verified

Company

Equity

Offered Verified - SEC 10-K source

Application

Cover letter

Not verified

Assessment

Not verified

Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

NASA Qaulity Data Analyst (Customer Onsite) Ellenwood, GA, United States Company Description: “We're not in the shipping business; we're in the information business” -Peter Rose, Expeditors Founder Global supply chain management is what we do, but at the heart of Expeditors you will find professionalism, leadership, and a friendly environment, all of which foster an innovative, customer service-based approach to logistics. 19,000 trained professionals 350+ locations worldwide Fortune 500 Globally unified systems Job Description: As the newly implemented Quality Management System (QMS) reaches General Availability globally, we are seeking a highly autonomous Quality Data Analyst to act as the primary engine for system stabilization and data extraction globally. Early-stage systems are notoriously complex and initially unstable; we need a tenacious data specialist who can navigate sparse documentation, extract fragmented data, and build a predictive data pipeline from the ground up. You will be the sole bridge connecting real-time warehouse floor errors directly to our engineering risk documentation, specifically Process Failure Mode and Effects Analysis (PFMEA). By standardizing the data to tell a cohesive story, bypassing the latency of traditional RCCA loops, and defining strict thresholds for risk updates, you will turn operational noise into actionable process improvements and prevent administrative chaos. Top Daily Responsibilities: Investigative System Stabilization: Navigate the newly launched, GA-stage QMS tool to extract, condition, and manage quality data, working through initial system instability and backend API learning curves to create reliable data pipelines. Data Standardization & KPI Alignment: Audit and unify core data streams, working directly with

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