Data Scientist; Continuous

Data Scientists at the US National Geospatial-Intelligence Agency (NGA) apply advanced mathematical, statistical, and scientific methods to convert national defense and intelligence questions into actionable insights. This open continuous announcement is designed to build a qualified applicant pool for future staffing needs.

This Open Continuous Job Announcement is used to establish a pool of qualified candidates. There is no immediate opening, and applications are reviewed when staffing needs arise. Multiple selections and placements may occur as positions become available across agency allocation.

• Develop and apply methods such as probabilistic modeling, AI/ML, and computer vision to identify, collect, process, and analyze large volumes of data to support actionable outcomes.
• Analyze data that may include imagery holdings, machine learning outputs, computer vision results, and other GEOINT mission datasets.
• Collaborate on teams integrated with analysts and other data professionals.
• Conduct data analysis across different systems.
• Model GEOINT mission data.
• Work with mission partners on their data needs.
• Provide complex solutions across deployed systems.
• Integrate new data into workflows already in use.

• Translate complex national defense and intelligence questions and business problems into actionable insights using advanced mathematical, statistical, and scientific techniques.
• Support mission areas that may include business analytics, model development offices, and GEOINT mission and data.

• Location: St. Louis, MO (onsite). Additional locations listed include Springfield, VA (1 vacancy).
• Telework eligible: No.
• Relocation expenses reimbursed: No.
• Salary: USD 76, per year.
• Pay scale & grade: IA 03.
• Promotion potential: 3.
• Work schedule: Full-time.
• Travel required: Not required.
• Appointment type: Permanent (Excepted Service).
• Occupations and job series: 1560 Data Science Series.
• Supervisory status: No.
• Drug test: Yes.
• Security clearance: Sensitive Compartmented Information.
• Announcement number: .
• Control number: .

This position is open to the public, including U.S. Citizens, Nationals, or individuals who owe allegiance to the U.S. External applicants only per agency clarification.

• US Citizenship is required.
• Designated or Random Drug Testing is required.
• Security investigation is required.
• Applicants must meet NGA fitness for employment standards.
• Direct Deposit is required.
• Trial period: NGA will evaluate your fitness and whether continued employment advances the public interest.

• Ability to obtain and retain a Top Secret security clearance with access to SCI
  .
• Retaining access requires a counterintelligence polygraph examination
  .
• Employees are subject to periodic random examinations to determine continued eligibility.
• Refusal to take the examination may result in denial of access to Top Secret information, SAP, or unescorted access to SCIFs.
• Employees with SCI access and under NGA cognizance must submit a Security Financial Disclosure Report (SF-714) annually.

• Demonstrated experience using structured or unstructured data for exploratory data analysis, classification, regression, and/or other statistical analysis.
• Experience analyzing, interpreting, and reporting on big data sets.
  
  Demonstrated experience cleaning, filtering, transforming, and/or enriching data.
• Demonstrated experience manipulating data using a programming language such as Python, R, SQL
  , or similar.
• Education requirement: Bachelor's degree from an accredited college or university in Mathematics, Data Science, Statistics, Computer Science, Geographic Information Science, Information Science, Informatics and Computing, or a related field that included at least 6 semester hours in statistics and 9 additional semester hours in scientific or technical coursework such as engineering, medicine, physical, biological, or social sciences.
• OR combination of education and experience: Minimum of 30 semester hours (45 quarter hours) equivalent to a major field of study in the listed areas, plus experience that included programming for data science (for example, Python, R) and a full range of professional statistical work.

• Ability to communicate technical methods and solutions to non-technical audiences verbally or in writing.
• Experience collaborating with experts in other fields to analyze and respond to…