Senior Data Analyst: AI/ML & Talent Analytics (TS/SCI)

i270 Solutions Group LLC

Virginia

On-site

USD 120,000 - 150,000

Full time

14 days+

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Job summary

i270 Solutions Group LLC is seeking a Senior Data Analyst to transform complex talent, language, and learning data into clear insights and actionable dashboards for a government program. You will develop and deliver AI-powered analytics and compelling briefing decks for leadership.

The role emphasizes direct client interaction, data storytelling, and rigorous data engineering practices, with a focus on quality, accessibility, and decision-ready outputs.

Qualifications

  • Active TS/SCI clearance with CI Poly required.
  • Bachelor’s or Master’s degree in data-related field preferred.
  • Experience in data analysis, analytics engineering and data visualization.

Responsibilities

  • Extract, transform, and visualize data from diverse sources to address talent, language, and learning questions for program leadership.
  • Build and maintain Tableau dashboards; develop user-friendly reports and briefing decks.
  • Apply advanced analytics, including AI/ML, to deliver timely, accurate insights.
  • Communicate findings clearly with clients and cross-functional teams to ensure decisions are data-driven.
  • Ensure deliverables are polished, accessible, and decision-ready with strong storytelling in code.

Skills

Data Engineering & ETL
Data Discovery
Advanced Analytics & AI
Tableau & Data Visualization
Reporting & Briefing
Microsoft Excel
Client Communication

Education

Bachelor's or Master's Degree in Data Science, Computer Science, Information Technology, Statistics, or a related field

Tools

JIRA

Job description

i270 Solutions Group LLC is seeking a Senior Data Analyst to transform complex talent, language, and learning data into clear insights and actionable dashboards for a government program. You will develop and deliver AI-powered analytics and compelling briefing decks for leadership.

The role emphasizes direct client interaction, data storytelling, and rigorous data engineering practices, with a focus on quality, accessibility, and decision-ready outputs.

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