Data Scientist

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 GS-11 CONSIDERATION: Applicants must have one year of specialized experience equivalent to the GS-09 grade level in the Federal service or equivalent responsibility in the private sector/pay systems.

This specialized experience must include all the following: Writing computer programs and algorithms using software/programming languages such as, but not limited to Python, R, SAS, and SQL. Cleaning/transforming data to address issues such as missing values, outliers, duplicates, functional dependencies, etc. Independently extracting and transforming data from relational databases using Python, R, SAS, or SQL. You must show specific examples of your experience and describe the systems you have utilized.

Reviewing software coding for accuracy. Your resume should show specific examples of using Python, R, SAS, or SQL. Developing visualizations that combine data from multiple sources using tools such as Python, R, Qlik, Tableau, or Power BI. OR 3 years of progressively higher level graduate education leading to a Ph.D. degree or Ph.D. or equivalent doctoral degree OR Combination of Experience and Education: You must have an appropriate combination of successfully completed graduate level education and experience.

The quality of the combination of education and experience must be sufficient to demonstrate that you possesses the knowledge, skills, and abilities required to perform work in the occupation. To determine your combination, first compute your experience as a percentage of the experience listed in the job announcement (1 year of specialized experience); then determine your education as a percentage of the education listed above; then add the two percentages. The total percentages must equal at least 100 percent.

Only graduate education in excess of 2 years (36 semester hours) may be used to qualify. FOR GS-12 CONSIDERATION: Applicants must have one year of specialized experience equivalent to the GS-11 grade level in the Federal service or equivalent responsibility in the private sector/pay systems. This specialized experience must include all the following: Writing computer programs and algorithms using software/programming languages such as, but not limited to Python, R, SAS, and SQL.

Cleaning/transforming data to address issues such as missing values, outliers, duplicates, functional dependencies, etc. Independently extracting and transforming data from relational databases using Python, R, SAS, or SQL. You must show specific examples of your experience and describe the systems you have utilized. Reviewing software coding for accuracy. Your resume should show specific examples of using Python, R, SAS, or SQL.

Developing visualizations that combine data from multiple sources using tools such as Python, R, Qlik, Tableau, or Power BI. Designing and implementing plans to accomplish analytic or computer programming projects. Leading data analysis projects to capture and implement data requirements and business rules. Education is not substitutable at the GS-12 grade level. Applicants must show 52 weeks specialized experience and the required education shown below in the education section.

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.

Analyze, interpret, review, and ensure integrity of, and review data.,Collaborate with subject matter experts and team members.,Conduct trend analysis.,Develop algorithms and analytical methods used in decision-making process.,Document data science requirements.,Generate business metrics.,Interpret data science requirements and make strategic recommendations.,Perform computer programming and data cleaning.,Present recommendations to management based on current analytics.,Provide recommendations for process improvements.,Utilize diverse analytical approaches.