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    Data Scientist - Washington, United States - Office of Personnel Management

    Office of Personnel Management
    Office of Personnel Management Washington, United States

    Found in: Talent US 2 C2 - 5 days ago

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    Description

    Summary

    As a Data Scientist at the GS , you will be part of Office of Workforce Policy and Innovation, Office of Personnel Management. If selected, you will be responsible for the use data science tools and analyses processes to develop models that form the foundation for evidence-based policy making and improve talent management activities governmentwide to shape the future of hiring for Federal jobs.

    Duties

  • Serve as the CAP technical expert in data science responsible for research, design, development, deployment, and enhancement of enterprise-wide analytics solutions using highly complex advanced analytics techniques such as machine learning, natural language processing, robotics process automation, and artificial intelligence to modernize classification and qualifications policy.
  • Apply expert knowledge of data science tools, including scripted languages (such as R, Python, SQL, and JavaScript), analytics platforms, and open source/commercial off the-shelf solutions to develop statistical software and computer programs. Performs analysis of statistical data and findings.
  • Design, develop, and implement computational and machine learning algorithms to big data, identifies insights, improves workflows and outcomes, conducts trend analyses, identifies new data sources, and defines new products using next generation analytics tools to develop data-driven organizational solutions to conduct occupational studies and for evidenced based policy making decisions.
  • Design and develop user-centric visualization (., dashboards) solutions that provide insights to decision makers using self-service data visualization tools such as Power BI, Tableau, and R Shiny applications.
  • Collaborate with others and leads teams and individuals to determine the best and most efficient ways to collect quantitative information, discusses results, shapes problems to one in which objective measurements can be identified and evaluated.
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