Armada-posted 3 days ago
Intern
Hybrid • Pittsburgh, PA

The Advanced Analytics Intern will support Armada’s Supply Chain Engineering team by assisting with data exploration, model development, and analytics enabling data-driven decisions across transportation, warehousing, procurement, and inventory operations. This role will work closely with engineers and analysts to build datasets, automate workflows, and generate insights using data science and machine learning techniques. Interns will gain hands-on experience with Snowflake, Python, SQL, Power BI, geospatial libraries, analytics workflows, and modern supply chain datasets used across Armada’s network.

  • Assist in structuring, validating, and analyzing large datasets from transportation, warehousing, freight, inventory, and supplier networks.
  • Support data cleaning, feature engineering, and exploratory analysis using SQL and Python.
  • Participate in the development and testing of statistical, geospatial, and machine learning models supporting operational decision-making.
  • Support creation of metrics, KPIs, and dashboards in Power BI or Python-based visualization libraries.
  • Apply supply chain knowledge to identify opportunities for cost improvement, service improvement, and process optimization.
  • Assist in automating data pipelines, report generation processes, or analytics workflows.
  • Contribute to development of templates, utilities, or documentation for repeatable analytics.
  • Work with internal stakeholders and data teams to align project priorities and deliverables.
  • Present findings to stakeholders in clear, concise formats suitable for business users.
  • Current coursework in Data Science, Analytics, Engineering, Computer Science, Supply Chain, Statistics, or a related bachelor’s program.
  • SQL experience.
  • Python (pandas, numpy; exposure to scikit-learn or geopandas a plus).
  • Experience working with large datasets in analytics projects.
  • Basic statistics, probability, and data validation practices.
  • Strong Excel skills.
  • Detail-oriented, data-driven approach to problem-solving.
  • Curiosity, initiative, and willingness to explore new tools and methods.
  • Ability to communicate technical insights in a clear business-friendly way.
  • Strong organizational and project management skills.
  • Ability to work independently and within a team environment.
  • Experience using analytics or modeling tools for logistics, transportation, or supply chain datasets.
  • Exposure to statistical modeling, forecasting, or machine learning concepts.
  • Experience with visualization tools (Power BI, Tableau, or similar).
  • Exposure to geospatial tools or concepts (ArcGIS, shapefiles, GIS libraries).
  • Familiarity with version control (GitHub, Azure DevOps).
  • Basic understanding of supply chain flows or logistics concepts.
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