Data Scientist

Assesses data sources to determine the type of data available and how data imports can be made into other systems to reduce or eliminate manual reporting requirements. Using exceptional knowledge of representative models, determines the adequacy of input data and ensures integrity and pertinence of output data.

Translate complex concepts, findings, and limitations into concise, plain language. Closely tie findings and conclusions into the agency mission, original problem statement and team objectives.

Research and design presentations and interpretations of analytical outputs tailored to specific audiences, including the use of interactivity and narrative storytelling where appropriate. Work with teams to develop data products and definitions.

Use appropriate analytic and statistical software to programmatically prepare data for analysis and clean imperfect data. Collaborate with teammates, customers, and stakeholders in a reproducible and organized manner. Produce expert technical guidance and recommendations for achieving the agency's objectives.

To evaluate your qualifications, your resume must clearly demonstrate how you meet the specialized experience described below. Your resume must not exceed two pages.

To ensure your qualifications can be fully evaluated, we recommend including the following information: Name, address, telephone number, email address; Job Title (if Federal Service, provide series and grade; if not in GS plan, provide GS equivalent grade); Relevant work experience—should include employer name, job title, start and end dates (month/year), the number of hours worked per week and descriptions that explain how you meet the required qualifications in the job announcement.

Education, certifications or licensures—If the job announcement requires any education, certifications or licensures, make sure to include the required information and any required documents like transcripts.

Your resume should contain enough information to make a valid determination that you fully meet experience requirements for each grade level you are applying to. If you do not provide enough information for us to determine your qualifications, you may be rated ineligible.

If you have volunteered your service through a National Service program (e.g., Peace Corps, Americorps), we encourage you to apply and include this experience on your resume. The GS-13 salary range starts at $108,173 per year. Locality pay will be determined upon selection.

If you are a new federal employee, your starting salary will likely be set at the Step 1 of the grade for which you are selected. To qualify, you must have at least one year of specialized experience equivalent to the GS-12 level or higher in the Federal service.

This position has a positive education requirement: Applicants must submit a copy of their college or university transcript(s) and certificates by the closing date of announcements to verify qualifications. If selected, an official transcript will be required prior to appointment.

BASIC REQUIREMENTS FOR DATA SCIENTISTS: 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 Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown in paragraph 1 above, plus additional education or appropriate experience SPECIALIZED EXPERIENCE: In addition to meeting the basic requirements, applicants must have at least one year of specialized experience equivalent to GS-12 grade level of the Federal service as defined.

Specialized experience is experience: Executing and managing program evaluation projects from design through implementation, data analysis, and reporting, utilizing systematic data collection to measure efficiency and effectiveness.

Adapting project designs and evaluation projects as necessary for randomized controlled trials (RCTs), qualitative studies, and other types of evaluations. Managing, merging, cleaning, and standardizing extensive structured and unstructured datasets at both enterprise and program levels to develop and produce derived metrics.

Utilizing scripting languages to gather and prepare data, and performing sophisticated statistical analyses using tools such as R or Stata. Developing comprehensive result summaries and evaluation presentations based on detailed data findings.