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Data Scientist (3 month opportunity)

Role overview

Qualifications

  • Bachelor’s degree in Data Science, Statistics, Computer Science, Human Resources Analytics, or a related field (Master’s preferred)
  • Strong proficiency in programming languages such as Python or R
  • Experience with natural language processing (NLP), machine learning, and data visualization
  • Knowledge of SQL and database management

Responsibilities

  • Collect, clean, and analyze large datasets related to position descriptions, job duties, and workforce information
  • Use statistical methods, natural language processing (NLP), and machine learning techniques to identify trends, patterns, and commonalities across job roles
  • Conduct text analytics on position descriptions to map tasks, skills, and responsibilities to appropriate job series and grade levels
  • Collaborate with human resources professionals, subject matter experts, and leadership to validate data-driven findings

Hard skills

Other skills

  • Collaboration
  • Analytical Skills
  • Problem Solving
  • Communication

About the company

Advent Services logo

Advent Services

Defense Technology

Advent is heavily invested in implementing new ideas, foster new approaches an utilize the latest technologies, as evidenced by our self-funded research and development of a geo-temporal analysis system utilizing AI/ML/NLP techniques for applications in Intelligence Analysis, Law Enforcement Investigation and Mental Health Research and Treatment.

Company details

IndustryDefense Technology
Company size11 - 50

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Job description

Position Title: Data Scientist

Position Overview: We are seeking a Data Scientist to support reclassification efforts across federal job series. The incumbent will apply advanced data analysis, statistical modeling, and computational techniques to workforce data and position descriptions, ensuring alignment with classification standards and helping inform accurate, data-driven decisions.

Required Qualifications:
• Bachelor’s degree in Data Science, Statistics, Computer Science, Human Resources Analytics, or a related field (Master’s preferred).
• Strong proficiency in programming languages such as Python or R.
• Experience with natural language processing (NLP), machine learning, and data visualization.
• Knowledge of SQL and database management.
• Ability to interpret and present complex data clearly to both technical and non-technical audiences.
• Strong analytical, problem-solving, and communication skills.

Key Responsibilities:
• Collect, clean, and analyze large datasets related to position descriptions, job duties, and workforce information.
• Use statistical methods, natural language processing (NLP), and machine learning techniques to identify trends, patterns, and commonalities across job roles.
• Conduct text analytics on position descriptions to map tasks, skills, and responsibilities to appropriate job series and grade levels.
• Collaborate with human resources professionals, subject matter experts, and leadership to validate data-driven findings.
• Develop dashboards, visualizations, and reports to communicate insights in a clear and actionable manner.
• Ensure consistency, accuracy, and compliance with federal classification policies and standards.
• Provide recommendations to leadership on job reclassification and series alignment based on data analysis.
• Stay current with emerging trends in workforce analytics, HR technology, and data science.

Desired Skills:
• Familiarity with federal job classification standards and Office of Personnel Management (OPM) guidance.
• Experience working with workforce or HR-related data.
• Knowledge of cloud computing environments and big data tools.
• Demonstrated ability to work collaboratively with cross-functional teams.
Impact: This position plays a key role in ensuring federal positions are accurately classified, improving workforce alignment, and enabling data-driven decision-making to support organizational goals.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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