Data Scientist

National-Oceanic-; Boulder (CO); On-site; USD 90,000 - 120,000; Full time

Job summary

NOAA NESDIS in Colorado is seeking qualified candidates for a data-focused role. The position requires one year of specialized experience at GS-12 level and a degree in a math, statistics, CS, or data science field, with proficiency in programming and data visualization tools.

Responsibilities include analyzing workforce data, building predictive models, and creating clear visualizations to communicate insights to leadership.

Qualifications

• One year of specialized experience equivalent to GS-12 in Federal service.
• Experience using statistical software to build models (R, Python, SAS, etc.).
• Ability to create infographics or reports conveying insights.

Responsibilities

• Analyze data related to workforce management.
• Develop predictive models or machine learning algorithms.
• Create infographics, visualizations, or reports conveying insights from data analysis.

Skills

Data analysis

Predictive modeling

Data visualization

Programming (R/Python/SAS)

Education

Bachelor's degree in Mathematics, Statistics, CS, Data Science

Combination of education and experience (30 semester hours)

Tools

R

Python

SAS

SPSS

STATA

Tableau

PowerBI

Job description

This position is located in the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service (NESDIS), with 2 vacancies in one of the listed locations.

Qualification requirements in the vacancy announcements are based on the U.S. Office of Personnel Management (OPM) Qualification Standards Handbook, which contains federal qualification standards. The handbook is available on the Office of Personnel Management's website located at: https://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/

BASIC REQUIREMENTS: This position requires applicants to meet the Basic Education Requirement in addition to at least one full year (52 weeks) of specialized experience in order to be found minimally qualified. Transcripts must be submitted with an application package. You MUST meet one of the following basic education requirements:

To qualify for the 1560 series: EDUCATION: A. Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.

OR

B. Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown in paragraph A above, plus additional education or appropriate experience.

-AND- SPECIALIZED EXPERIENCE: Applicants must possess one year of specialized experience equivalent in difficulty and responsibility to the next lower grade level in the Federal Service. Specialized experience is experience that has equipped the applicant with the particular competencies/knowledge, skills and abilities to successfully perform the duties of the position. This experience need not have been in the federal government.

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; knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.

To qualify at the ZP-4 or GS-13 level: SPECIALIZED EXPERIENCE: In addition to meeting the Basic Requirement above, applicants must also possess one full year (52 weeks) of specialized experience equivalent to the ZP-3 or GS-12 in the Federal service. Specialized experience MUST include all of the following:

• Analyzing data related to workforce management;
• Utilizing programming or statistical software suites (i.e. R, Python, SAS, SPSS, STATA, Tableau, PowerBI, etc.) to construct predictive models or machine learning algorithms; and
• Creating infographics, visualizations, or reports conveying insights derived from data analysis.