Data Analyst, Quality

ABOUT THE SITE

Anduril, a leader in autonomous systems and weapons manufacturing, is building Arsenal-1, its first hyperscale manufacturing facility, just south of Columbus, Ohio in Pickaway County. Arsenal-1 is redefining the scale and speed that autonomous systems and weapons can be produced for the United States and its allies and partners. This is a monumental and essential step toward rebuilding America’s defense industrial base, strengthening America’s warfighting capabilities, and enhancing deterrence amid rising international threats.

ABOUT THE TEAM

Quality Intelligence supports data and AI in Anduril's manufacturing quality organization through three distinct areas: Analytics, Manufacturing AI, and Vision Inspection. Analytics owns end-to-end data and analytics work that directly drives impact for Anduril's product quality engineers on the factory floor. Our customers are program quality leaders, manufacturing engineers, and operators across sites and programs. The work encompasses building scorecards that catch quality drift before customers do, pipelines that turn ERP / MES / QMS data into decisions, and AI tools that compress hours of manual triage into minutes.

We operate hub-and-spoke. HQ builds platform-grade analytics centrally; site engineers localize and run them at each manufacturing site. This is the site applications lead role at Arsenal-1, Anduril's high-volume manufacturing site in Ashville, OH. You are the resident analytics engineer at the site and the person accountable for what Quality Intelligence has deployed there. Most of this role is hands-on build; the rest is running the site as a program: gathering requirements from the floor, sequencing the work, driving rollouts to completion, and feeding what you learn back into the HQ roadmap. Arsenal 1 is a lighthouse site, so the patterns you set here become the template for the factories that follow.

This role is subject to ITAR. Applicants must be eligible to obtain and maintain a U.S. Government security clearance.

WHAT YOU’LL DO 

• Intersection of Analytics and Manufacturing: You will work at the intersection of hardware manufacturing and data analytics. You are not afraid to spend time on the shop floor learning quality workflows, building analytics tools, and turning what you observe into well-designed, actionable dashboards.
• Production Data: You'll pull from production systems (ERP, MES, QMS, inventory), help build pipelines and ontologies in Palantir Foundry and Databricks, and partner with manufacturing engineers, ML practitioners, and program quality leads to ship analytics products operators depend on.
• Build & Maintain Analytics for Arsenal-1: You will help design, build, and maintain the production dashboards, pipelines, and quality metrics the site runs on. Arsenal-1 is greenfield, so you will collaborate closely with HQ to port over proven work and adapt it to site-specific needs.
• Support intake and requirements: participate in feedback loops with operators, manufacturing engineers, and program quality. Help translate what you hear into backlog items -- what can be configured this week, what needs HQ build time, and what we are deliberately not doing.
• Investigate data quality: When a dashboard is inaccurate or a number looks wrong, dig in. Run deep-dive analysis in SQL and Python, trace problems through the stack, identify the root cause, and work with the team to fix it at the source.
• Contribute to technical improvements: Help implement data-quality checks, validation rules, and automated monitoring directly in the pipelines. Your data is trusted because it is provably trustworthy.
• Build AI-assisted analytics tools: small apps and workflows in Foundry / Databricks that reduce repetitive analyst work, grounded in what you have learned from operators on the floor.
• Support data projects end-to-end: partner with cross-functional teams from requirements through deployment. Help translate program quality leads' problems into data products and support rollout efforts.
• Drive adoption: a dashboard nobody opens is ineffective. You will help train operators, run office hours, track usage, and treat adoption at Arsenal-1 as a deliverable, not a downstream side effect.
• AI Use: You will be expected to use AI aggressively in your own work -- to draft pipelines, write tests, generate dashboards, explore unfamiliar data, and accelerate the repetitive parts of the job.
• Collaboration: Collaborate with cross-functional teams, which requires regular interaction with production and manufacturing stakeholders and frequently working directly on the production floor.

REQUIRED QUALIFICATIONS

• Bachelor's degree in Computer Science, Data Science, Industrial Engineering, Mechanical Engineering, or a related technical field from an accredited program. Recent graduates (0-2 years of experience) are encouraged to apply.
• Demonstrated interest or coursework in data engineering, analytics, or applied data science -- through internships, co-ops, capstone projects, or personal projects.
• Curiosity about how manufacturing works: the workflows, the quality gates, and how data drives or degrades quality outcomes. Willingness to work in and around manufacturing operations, including time on the production floor.
• Proficiency in SQL: comfortable writing queries across multiple tables, using joins, aggregations, and window functions.
• Familiarity with at least one programming language for data work (Python preferred).
• Comfort using AI tools (Cursor, Claude Code, Copilot, ChatGPT) and an ability to review AI-generated output critically. You have a sense of where these tools help and where they fall short.
• Strong problem-solving instincts: when a number looks wrong, your first impulse is to figure out why.
• Eligible to obtain and maintain a U.S. Government security clearance (this role is subject to ITAR).
• You communicate plainly: to a director without jargon, to an engineer without losing precision.
• Based in or willing to relocate to the greater Columbus, OH area and work on-site at Arsenal-1 in Ashville, OH.
• Travel up to 25% to Anduril sites and vendors.
• U.S. citizenship is required pursuant to contractual obligations.

PREFERRED QUALIFICATIONS

• Internship or co-op experience in a manufacturing, industrial, or hardware engineering environment.
• Exposure to any of: ERP (Oracle, NetSuite, SAP), MES, QMS, PLM (Teamcenter), or inventory / warehouse systems.
• Experience with a cloud data platform (Databricks, Foundry, Snowflake, BigQuery, or similar) -- even in a classroom or personal project setting.
• Python for data transformation and scripting (Pandas, PySpark, or equivalent).
• Familiarity with quality methodologies: RCCA / 8D, FMEA, GD&T, IQC / OQC, or statistical process control.
• Defense or regulated-manufacturing exposure (ITAR, AS9100, IPC-610, MIL-STD-1916, or similar).
• Software engineering practices: Git, code review, CI, and testing data code with the same rigor as application code.
• Interest in integrating LLMs or ML models into analytics workflows.