Senior Data Scientist

Perform data cleaning and visualization, trend analysis, and algorithm development.

Develop new prescriptive analytics used in decision making.

Present alternate solutions to analytics and future concepts.

Develop statistical and machine learning models.

Interpret policy and regulatory requirements.

Develops recommendations for data collection activities and data integration.

Develops usage and control policies.

Communicates in writing to internal and external individuals.

Analyzes outputs from analyses.

Leads the design for data enhancement.

Provides education on new approaches to data anlysis.

Applicants must meet all qualifications and eligibility requirements by the closing date of the announcement including specialized experience and/or education, as defined below.

For the GS-14 grade level: Applicants must have one year of specialized experience (equivalent to the GS-13 grade level) that demonstrates: Using Python or R in support of data analytics projects. Developing and executing approaches for analyzing, interpreting, visualizing, and verifying complex data and analyses.

Leading projects by establishing objectives, assigning responsibilities, reviewing deliverables, and offering expert guidance on analytical programming, statistical techniques, and data visualization strategies.

Developing oral and written presentations communicating complex and technical analyses to inform, influence, and persuade a variety of audiences.

Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community, student, social).

Volunteer work helps build critical competencies and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.