Global Director, Production Analytics & Insights

Anduril Industries

Costa Mesa (CA)

On-site

USD 180,000 - 240,000

Full time

3 days ago
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Benefits offered by this job

Equity grants
Health benefits
Career growth

Job summary

Anduril Industries seeks a Director, Production Analytics to own global analytics across manufacturing engineering, operations, supply chain, planning, and warehousing. You will tackle the organization’s hardest problems with hands-on analytics and build a team that can run multiple programs in parallel.

The ideal candidate combines deep analytical method with leadership, can translate data into strategic decisions, and will ensure trusted metrics by cleaning and standardizing data before

Qualifications

  • 10+ years in analytics, data, or quantitative operations, including 5+ years leading analytics or data teams, and experience managing managers or clear readiness to do so.

Responsibilities

  • Apply analytics to production’s biggest problems with evidence-backed prioritization.
  • Shift production reporting from retrospective to leading indicators; identify risks early.
  • Generalize proven capabilities into enterprise-standard products and consolidated reporting.
  • Scale ramp analytics from low to high rate and maintain a current view of constraints.
  • Build the analytics organization and manage the managers within it.
  • Ensure metrics are trusted; fix data defects before modeling.

Skills

Analytics leadership
SQL
Data stack
Problem solving
Stakeholder influence

Tools

Databricks
Palantir Foundry
SQL tooling

Job description

Anduril Industries seeks a Director, Production Analytics to own global analytics across manufacturing engineering, operations, supply chain, planning, and warehousing. You will tackle the organization’s hardest problems with hands-on analytics and build a team that can run multiple programs in parallel.

The ideal candidate combines deep analytical method with leadership, can translate data into strategic decisions, and will ensure trusted metrics by cleaning and standardizing data before

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