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Salary
≈ $53k – $87k per year (Estimated)
Location
In office (San Diego)
Seniority
Intern
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H-1B filings in 12 months: 2
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Internship

Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Oct 21, 2026. Shield AI scores B on the Alion truth index.

Overview
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Shield AI is an American defence technology company founded in 2015 that builds autonomy software and uncrewed aircraft for military missions. Its Hivemind autonomy stack lets aircraft fly, navigate and complete objectives without GPS, a remote pilot or a communications link, which matters in contested environments where those links are jammed. Headquartered in San Diego, California, the company fields the V-BAT vertical take-off aircraft with United States and allied forces, licenses Hivemind to other manufacturers and is developing the X-BAT jet for high-end missions.

Shield AI is seeking a Data Science Intern to assess data readiness and develop predictive forecasting capabilities for Anaplan. Working with Finance and engineering mentors, you will build and evaluate models, then prepare their outputs for integration into existing planning models. Your work will advance the vision of an autonomous, continuously updated forecast that reduces preparation effort and gives the executive team and board access to current, governed projections.

What you'll do

  • Assess financial and operational data for predictive readiness, identifying useful drivers and material gaps.
  • Build baseline and machine-learning forecasts for a focused Finance use case.
  • Evaluate accuracy, stability, and explainability using appropriate backtesting.
  • Prepare model outputs for Anaplan consumption and demonstrate an integration prototype with the team.
  • Recommend the data, monitoring, and review practices needed to support reliable forecast updates.
  • Present findings and deliver documented, reproducible work that informs the next stage of development.

Required qualifications

  • Pursuing a Bachelor's or Master's degree in data science, statistics, computer science, applied mathematics, economics, or a related field.
  • Coursework or project experience with Python, SQL, statistics, and predictive modeling.
  • Ability to assess data quality and communicate model assumptions and limitations.

Preferred qualifications

  • Experience with time-series forecasting, feature engineering, or model evaluation.
  • Familiarity with Databricks, financial data, or enterprise planning.
  • Interest in integrating machine learning into practical business workflows.
  • Strong curiosity, collaboration, and problem-solving skills.
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