Residential Data Analyst Intern

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  "last_changed_at": "2026-05-29T07:01:10.167Z",
  "active_status": "active"
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    "region": null,
    "country": "United States",
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  "inferred_at": "2026-06-06T20:29:41.602Z",
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      "United States"
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  "remote_policy": "remote",
  "salary_period": "year",
  "workplace_type": "remote",
  "salary_currency": "USD"
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{
  "lists": [
    {
      "text": "",
      "content": "<h3><strong>Qualifications</strong></h3>\n\n<li>\n<p>Currently pursuing a degree in a quantitative or technical field (data science, statistics, computer science, engineering, economics, or similar)</p>\n</li>\n<li>\n<p>Proficiency with SQL — comfortable writing joins</p>\n</li>\n<li>\n<p>Working knowledge of Python for data analysis (pandas, basic API calls, light scripting)</p>\n</li>\n<li>\n<p>Strong instinct for how to link datasets together — you can look at two sources and quickly identify the keys, the gaps, and the gotchas</p>\n</li>\n<li>\n<p>Relentless attention to detail. When numbers don't tie out, you want to know why</p>\n</li>\n<li>\n<p>Self-starter who takes ownership beyond your immediate scope; when you see a problem, you drive it to resolution rather than assuming someone else will</p>\n</li>\n<li>\n<p>Intellectual curiosity about energy markets, distributed energy resources, or the residential clean-energy space is a strong plus</p>\n</li>\n<li>\n<p>Gritty and collaborative — kind in your interactions, focused on winning as a team</p>\n</li>\n"
    }
  ],
  "country": "US",
  "createdAt": 1779848975654,
  "updatedAt": null,
  "categories": {
    "team": "Partnerships",
    "location": "Remote",
    "commitment": "Coop/Intern",
    "department": "Sales",
    "allLocations": [
      "Remote"
    ]
  },
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