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DISA Technologies, Inc.
DISA Technologies, Inc.
51 – 200 Employees
B2BHardwareScience
DISA Technologies, Inc. is a science and hardware company developing mineral-processing technology for mining and resource operators. Its patented DISA Tech™ platform uses High-Pressure Slurry Ablation to liberate valuable minerals through high-velocity slurry collisions, with the aim of reducing energy use and limiting the fines and slimes associated with conventional grinding. The company’s modular systems are designed for deployment across active ore bodies, stockpiles, tailings, and legacy uranium sites, supporting improved downstream concentration through processes such as flotation and leaching while combining resource recovery with onsite remediation.
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Data Engineering and Machine Learning Intern – Hybrid

Organize and standardize DISA Technologies’ mineral-processing test data for cloud analytics. Analyze historical records to assess data quality and identify machine-learning-ready relationships.

USUnited StatesWYWyoming
$20 / year
HybridContractEntry levelNo degree requiredEnglish RequiredData Engineer
PandasPythonSQL

Description

  • Catalog historical data sources with details such as location, client, project, site or program, equipment unit, date range, format, and completeness.
  • Document specifications for recurring record formats and include representative files.
  • Convert test files into a standardized tabular template and place them in the assigned staging area.
  • Create data-quality reports that flag missing information, incomplete or questionable analyses, and inconsistencies across files.
  • Explore datasets to uncover potential correlations and relationships.
  • Prepare feasibility memos explaining which questions the historical data can and cannot answer.
  • Standardize file names and tags in legacy folders when needed.
  • Assemble metadata required for migration to a document-management system when needed.
  • Match test records with related measurement datasets when needed.

Requirements

  • Currently pursuing or recently completing a degree in computer science, data science, statistics, engineering, or a related discipline.
  • Proficiency with Python and pandas, or an equivalent toolset, for reading, cleaning, and reshaping tabular data.
  • Hands-on experience handling untidy real-world files, including Excel workbooks, CSVs, PDFs, and inconsistent naming or structures.
  • Methodical and detail-oriented, with a willingness to record missing information and unresolved inconsistencies.
  • Able to work independently from defined schemas and templates, while seeking clarification when files do not conform.
  • Strong written communication skills.
  • Familiarity with SQL, data catalogs, or data-lake concepts such as bronze, silver, and gold layers.
  • Basic statistics or exploratory data-analysis experience using tools such as matplotlib, seaborn, or Jupyter.
  • Interest in mineral processing, chemistry, or industrial process data; previous domain expertise is not required.
  • Power-user familiarity with SharePoint or OneDrive.

Benefits

  • A managed laptop or virtual desktop is provided.
  • A confidentiality acknowledgment is required because the role involves confidential client data.

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