Human Capital Analytics Expert

Golden Key Group

$110K — $130K *
US-AnywhereRemote in Virginia, US
Education, Government & Non-Profit
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor’s degree in Statistics, Data Science, Mathematics, or related field.
  • Active TS/SCI clearance with a current polygraph.
  • 4+ years of experience in data analysis and modeling.
  • 3+ years developing automated HR dashboards for executives.
  • 3+ years querying databases using SQL.
  • 2+ years using scripting languages like Python or R.
  • 3+ years cleaning and normalizing large datasets.

Responsibilities

  • Serve as an expert in Human Capital data analytics and visualization.
  • Build predictive analytics models supporting HR decisions.
  • Develop automated performance dashboards for executives.
  • Coordinate with IT to resolve data issues and enhance capabilities.
  • Query and analyze complex HR datasets.
  • Automate data processes and reporting workflows.
  • Present data-driven recommendations to agency leaders.

Benefits

  • Work on impactful projects supporting federal agencies.
  • Opportunity for potential future contract roles.
  • Collaboration with technical teams in a leading intelligence agency.
  • Engagement in advanced data methodologies, including AI and machine learning.
Full Job Description
Overview

We are seeking an experienced Human Capital Analytics Expert to support a federal intelligence agency in Springfield, Virginia. This individual will serve as a subject matter expert in data analytics, data modeling, statistics, and data visualization, helping agency leaders make informed, data-driven workforce decisions.

 

The Human Capital Analytics Expert will develop statistical and predictive models, create executive-level Human Resources dashboards, integrate data from multiple systems, and recommend process and performance improvements. The ideal candidate combines advanced technical expertise with the ability to translate complex analytical findings into clear, actionable recommendations for technical and non-technical audiences.

 

Location: Springfield, VA

 

Position is expected to start early 2027

 

This position is being recruited in support of potential future contract awards, and qualified candidates may be considered for upcoming opportunities supporting federal government clients.

 

Responsibilities
  • Serve as a subject matter expert in Human Capital data analytics, data modeling, statistics, and data visualization
  • Build and modify statistical and predictive analytics models, algorithms, queries, and methodologies that support Human Resources decision-making
  • Develop automated Human Resources performance dashboards for executive-level audiences
  • Support the maintenance and advancement of the agency’s Human Capital data ontology
  • Coordinate with agency information technology teams to identify and resolve data issues, including data migration, validation, integration, and new capabilities
  • Query, extract, transform, clean, normalize, and analyze complex Human Resources datasets
  • Integrate data from multiple Human Resources systems and other relevant sources
  • Automate data processes, analytical workflows, reporting, and dashboard production
  • Identify trends, patterns, risks, and opportunities within workforce data
  • Recommend process and performance improvements based on analytical findings
  • Ensure all reports, dashboards, and analytical deliverables meet established quality and performance requirements
  • Apply artificial intelligence, machine learning, and large language model techniques to enhance Human Resources analytics capabilities and automate complex workflows
  • Generate predictive workforce insights to support strategic workforce planning and decision-making
  • Present complex findings and data-driven recommendations to agency leaders and non-technical audiences
  • Maintain effective communication with agency leaders, managers, technical teams, and subordinate personnel
  • Follow applicable data governance, privacy, security, and records-management requirements
Qualifications
  • Bachelor’s degree or higher in Statistics, Data Science, Mathematics, Computer Science, Information Systems, Economics, or a related discipline from an accredited institution
  • Active TS/SCI clearance with a current polygraph
  • Minimum of four years of experience in data analysis and data modeling
  • At least three years of experience developing automated Human Resources performance dashboards for executive-level audiences
  • At least three years of experience querying databases using SQL
  • At least two years of experience using data-manipulation or scripting languages such as Python, R, or SAS
  • At least three years of experience handling, cleaning, and normalizing large, complex datasets containing one million or more records
  • Experience integrating data from multiple Human Resources systems
  • Advanced proficiency with data-visualization and business-intelligence tools such as Tableau or Power BI
  • Demonstrated ability to automate data processes, reports, and analytical workflows
  • Ability to communicate complex analytical findings clearly to non-technical audiences
  • Experience developing and presenting data-driven recommendations to agency leaders
  • Strong analytical, problem-solving, data-quality, and documentation skills
  • Ability to work full-time on-site in Springfield, Virginia

 

Desired Qualifications
  • At least two years of experience working with federal Human Resources Information Systems, such as PeopleSoft, Oracle Human Capital Management, or Workday
  • Knowledge of federal data-governance, privacy, and security requirements
  • At least two years of experience using artificial intelligence, machine learning, or large language modeling
  • Experience applying predictive analytics to workforce planning, talent management, retention, or organizational performance
  • Familiarity with Human Capital data ontologies, data architecture, or enterprise data-integration practices
  • Previous experience supporting the Intelligence Community

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