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Mathematics Statistician Or Statistician (Data Scientist) Direct Hire

Internal Revenue Service | Johnstown, PA

Posted Date 6/06/2023
Description Positions under this announcement are being filled using a Direct Hire Authority (DHA). For information on the Recruitment Incentive please reference the Additional Information section of this announcement.

Click on "Learn more about this agency" button below to view Eligibilities being considered and other IMPORTANT information.

WHERE CAN I FIND OUT MORE ABOUT OTHER IRS CAREERS? Visit us on the web at www.jobs.irs.govWHAT IS THE LARGE BUSINESS AND INTERNATIONAL (LB&I) DIVISION?
WHAT IS THE RESEARCH, APPLIED ANALYTICS, & STATISTICS (RAAS) DIVISION?
WHAT IS THE TAX EXEMPT/GOVERNMENT ENTITIES (TEGE) DIVISION?
WHAT IS THE SMALL BUSINESS/ SELF EMPLOYED (SB/SE) DIVISION?
WHAT IS THE HUMAN CAPITAL OFFICE (HCO) DIVISION?
WHAT IS THE WHISTLEBLOWER OFFICE (WO) DIVISION?

A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

50 Vacancies will be filled in the following specialty areas: Large Business and International (LB&I), and Research, Applied Analytics and Statistics (RAAS).

2 Vacancies will be filled in the following specialty area: Tax Exempt and Government Entities Compliance Planning & Classification CP&C.

3 Vacancies will be filled in the following specialty area: Small Business Self Employed (SB/SE) Operations Support, Operations Support Business Development Office

The following are the duties of this position at the full working level. If this vacancy includes more than one grade and you are selected at a lower grade level, you will have the opportunity to learn to perform these duties and receive training to help you grow in this position.
  • Serves as a technical expert with responsibility for the initiation, planning, implementation, controlling, modifying and executing of all or part of an entire project, including such tasks as formulation of workload estimates for program segments, specification of the methodology to be used, preparation of appropriate specifications and procedures, and review of computer systems specifications and materials and instructions needed for assuring the adequacy of the project's design and objectives. Explores novel methods of retrieving data, and develops innovative recommendations to management and senior leadership as a means for making data driven decisions such as modification of processes and policies. Reviews, evaluates, validates, and documents the results of the findings.
  • Assists the supervisor in determining the scope, goals and schedules for future programs in the Office. Results have a direct impact on assigned area's policy. Acts as a troubleshooter in resolving bottlenecks at any step in a project by identifying and proposing solutions; this may include coordination with other project team members or stakeholders to mitigate issues.
  • Collaborates with business and technology partners to understand business needs, identify opportunities, and develop and implement analytical solutions.
  • Identifies and assesses relevant data sources' validity and reliability to meet project needs.
  • Collates, cleans, transforms, analyzes, and integrates structured and unstructured data from various sources in preparation for analysis.
Federal experience is not required. The experience may have been gained in the public sector, private sector or Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/year, and indicate number of hours worked per week, on your resume.

You must meet the following requirements by the closing date of this announcement AND/OR time of referral:

IOR BASIC REQUIREMENTS GS-1530 Statistician (Data Scientist):You must have a degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.

OR

COMBINATION OF EXPERIENCE AND EDUCATION: courses as shown above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.

IOR BASIC REQUIREMENTS GS-1529 Mathematical Statistician (Data Scientist): You must have a degree that included courses in mathematics and statistics totaling at least 24 semester hours. This course work must have included a minimum of 12 semester hours of mathematics and 6 semester hours were in statistics. Courses acceptable toward meeting the mathematics course requirement must have included at least four of the following: differential calculus, integral calculus, advanced calculus, theory of equations, vector analysis, advanced algebra, linear algebra, mathematical logic, differential equations, or any other advanced course in mathematics for which one of these was a prerequisite. Courses in mathematical statistics or probability theory with a prerequisite of elementary calculus or more advanced courses will be accepted toward meeting the mathematics requirements, with the provision that the same course cannot be counted toward both the mathematics and the statistics requirement.

OR

COMBINATION OF EXPERIENCE AND EDUCATION: includes at least 24 semester hours of mathematics and statistics, including at least 12 hours in mathematics and 6 hours in statistics, as described above; and Experience that showed evidence of statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying known statistical techniques to data such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.

AND

GS-1529/1530-11 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-09 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  2. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  3. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  4. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  5. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  6. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
OR

EDUCATION: You may substitute education for specialized experience specialized experience as follows: Three (3) full academic years of progressively higher-level graduate education in Mathematics, statistics, or related fields. OR Ph. D. or equivalent doctoral degree Mathematics, statistics, or related field of study from an accredited college or university.

OR
COMBINATION OF EXPERIENCE AND EDUCATION: A combination of qualifying graduate education and experience equivalent to the amount required.

GS-1529/1530-12 SPECIALIZED EXPERIENCE: To be eligible for this position at this grade level, you must meet the following requirements. In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-11 grade level in the Federal service. Examples of specialized experience for this position may include:
  1. Experience applying knowledge of statistical theories, principles, concepts and practices that relate to experimental design, data analysis, sampling, forecasting, quality control, and operations research to understand, model and improve program operations.
  2. Experience using data mining process models (such as CRISP-DM, SEMMA, etc.,) to design and execute data science project.
  3. Experience preparing and analyzing structured and unstructured datasets to explorations and evaluating data science centric models.
  4. Experience applying a range of analytic approaches, including (but not limited to) machine learning, text analytics, and natural language processing; graph theory, link analysis and optimization models; complex adaptive systems; and/or deep learning neural networks that are part of the exploration.
  5. Experience coding in various programming languages (such as R, Python, SQL, or JAVA) to conduct various phases of data science projects.
  6. Experience creating and querying different datastores and architectures (such as Sybase, Oracle, and open-source databases) to work with various types of data as part of the data science project.
  7. Experience using tools for data visualization (graphs, tables, charts, etc.,) and end-user business intelligence.
Please see Education Section for additional qualification on the GS-13.

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