Responsibilities

At NSA Data Science is a broad field, and a team effort, spanning all the expertise needed to derive value from data. As a Data Scientist specializing in Machine Learning Operations (ML Ops) Engineering, you will help deploy and maintain ML systems that keep NSA at the cutting edge of intelligence gathering and reporting, with all the high-functioning support processes that it requires. Responsibilities include: - Implementing ML pipeline and workflows - Deploying, monitoring, and maintaining ML models in production systems - Deploying ML services and applications to secure cloud platforms (e.g., AWS, Azure, GCP, IBM Cloud) - Building and deploying micro-services as part of ML/DSci applications - Building continuous integration and delivery pipelines for ML applications - Ensuring security and compliance of ML systems - Communicating with a team of data scientists, data engineers, and stakeholders; documenting the process

Job Summary

Depending on the skill-sets currently in demand, newly hired ML OPS Engineers may be assigned to a mission office, or alternatively enrolled in the three-year Data Science Development Program (DSDP) in which they will both broaden and specialize their data science skills by taking courses and touring with a variety of mission offices (each for several months). In either case you will work with NSA experts in ML OPS engineering, related technical domains, and specialized subject areas. You will have opportunities to participate in internal technical roundtables, and to attend technical conferences with experts from industry and academia.

Qualifications

Applicants will be asked to complete the Data Science Examination (DSE) evaluating their knowledge of statistics, mathematics, and computer science topics that pertain to data science work. Passing this examination at a local testing site is a requirement in order to be considered for selection into a data scientist position. Upon passing the examination, applicants will be evaluated for the minimum qualifications outlined in this ad. Transcripts will be requested prior to being invited to interview with Agency data science professionals. The qualifications listed below are the minimum acceptable to be considered for the position. Degree must be in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. A degree in a related field (e.g., Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines (i.e., behavioral, social, library, and life) may be considered if it includes a concentration of coursework (typically 5 or more courses) in advanced mathematics (typically 200 level or higher; such as calculus, differential equations, discrete mathematics, linear algebra, and calculus based statistics) and/or computer science (e.g., algorithms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math courses intended to meet a basic college level requirement, or upper level math courses designated as elementary or basic do not count. Note: Degrees in related fields will be considered if accompanied by a Certificate in Data Science from an accredited college/university. Relevant experience must be in one or more of the following (for Entry level) but in two or more for Full Performance, Senior, and Expert levels: designing/implementing machine learning, data mining, advanced analytical algorithms, programming, data science, advanced statistical analysis, artificial intelligence, computational science, software engineering, or data engineering. ENTRY/DEVELOPMENTAL Entry is with a Bachelor's degree and no experience. An Associate's degree plus 2 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position. FULL PERFORMANCE Entry is with a Bachelor's degree plus 3 years of relevant experience or a Master's degree plus 1 year of relevant experience or a Doctoral degree and no experience. An Associate's degree plus 5 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position. SENIOR Entry is with a Bachelor's degree plus 6 years of relevant experience or a Master's degree plus 4 years of relevant experience or a Doctoral degree plus 2 years of relevant experience. An Associate's degree plus 8 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position. EXPERT Entry is with a Bachelor's degree plus 9 years of relevant experience or a Master's degree plus 7 years of relevant experience or a Doctoral degree plus 5 years of relevant experience. An Associate's degree plus 11 years of relevant experience may be considered for individuals with in-depth experience that is clearly related to the position.

Pay, Benefits, & Work Schedule


Salary offers are based on candidates' education level and years of experience relevant to the position and also take into account information provided by the hiring manager/organization regarding the work level for the position. This is a full-time position, hiring for the Maryland, Colorado & Hawaii locations. Salary ranges vary by work level. Salary range: $81,233 - $183,500 (Entry/Developmental, Full Performance, Senior, Expert) On the job training, internal NSA courses, and external training will be made available based on the need and experience of the selectee. Typical work schedule is Monday - Friday, with basic 8 hr/day requirements between 0600 to 1800 (flexible).


How To Apply - External


Apply soonest, as job postings can close earlier than stated end dates due to changes in requirements. It is important to review and note the minimum qualifications, as only those applicants who meet the required qualifications will be contacted to continue the employment process. Please populate the resume tool to showcase any relevant work experience and education related to the position and answer any applicable screening questions. Information collected will be used to determine eligibility, and failure to provide accurate information may result in disqualification for this position. A confirmation email will be sent after submission of the first application and also after any future updates to submitted applications. **Due to time sensitive communications regarding applications, please ensure your spam filters are configured to accept email from noreply@intelligencecareers.gov. For job vacancies that include stated testing requirements, also include the following: @uwe.nsa.gov, @nsa.gov, and @pearson.com** U.S. Citizenship is required for all applicants. NSA is an equal opportunity employer and abides by applicable employment laws and regulations. All applicants and employees are subject to random drug testing in accordance with Executive Order 12564. Employment is contingent upon successful completion of a security background investigation and polygraph. Reasonable accommodations may be provided to applicants with disabilities during the application and hiring process where appropriate. Please visit our Diversity link for more information https://www.intelligencecareers.gov/NSA/diversity-and-inclusion.


DCIPS Disclaimer


The National Security Agency (NSA) is part of the DoD Intelligence Community Defense Civilian Intelligence Personnel System (DCIPS). All positions in the NSA are in the Excepted Services under 10 United States Codes (USC) 1601 appointment authority. DoD Components with DCIPS positions apply Veterans' Preference to eligible candidates as defined by Section 2108 of Title 5 USC, in accordance with the procedures provided in DoD Instruction 1400.25, Volume 2005, DCIPS Employment and Placement. If you are a veteran claiming veterans' preference, as defined by Section 2108 of Title 5 U.S.C., you may be asked to submit documents verifying your eligibility.

Skills

The ideal candidate has a desire for continual learning along with excellent analytical, problem-solving, communication (oral and written), and interpersonal skills who is: - Accountable - Proactive - Detail oriented - Able to solve complex problems - Proficient with critical thinking and reasoning to make analytic determinations - Effective at working in a collaborative team environment - Able to bridge the gap with both technical and non-technical audiences Knowledge, skills, and relevant experience in one or more of the following is required: - Designing and implementing machine learning - Data mining - Advanced analytical algorithms - Programming - Data science - Advanced statistical analysis - Artificial Intelligence - Computational science - Software engineering - Data engineering

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