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Statistical Engineering Jobs in Raleigh, NC (NOW HIRING)

SP II

Durham, NC · On-site

Provide statistical programming support in the project specific programming of statistical tables, listings, figures, and analysis datasets for clinical trials in accordance with Good Clinical ...

Posted today

SP II

Durham, NC · On-site

Provide statistical programming support in the project specific programming of statistical tables, listings, figures, and analysis datasets for clinical trials in accordance with Good Clinical ...

Posted today

Provide administrative and functional oversight for the biostatistics and statistical programming (BioSP) functions of the organization. Works with Executive Director and/or Chief Scientific Officer ...

Advanced programming skills in a statistical programming language, such as SAS, R, or Python. Ability to write computer code to perform analysis on complex modeling and analytical challenges and to ...

The GPS AI & Data Engineering offering is responsible for developing advanced analytics products and applying data visualization and statistical programming tools to enterprise data in order to ...

Have proficiency in statistical programming (e.g., R, SAS, STATA, or Python) * Have interest or experience in cancer epidemiology, genomics, and/or social determinants of health * Exhibit strong ...

Have proficiency in statistical programming (e.g., R, SAS, STATA, or Python) * Have interest or experience in cancer epidemiology, genomics, and/or social determinants of health * Exhibit strong ...

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Statistical Engineering information

What are the key skills and qualifications needed to thrive as a Statistical Engineer, and why are they important?

To thrive as a Statistical Engineer, you need strong quantitative analysis skills, a background in statistics or mathematics, and often a relevant degree such as in engineering or applied statistics. Proficiency with statistical software (e.g., R, SAS, Python), data management systems, and sometimes Six Sigma certification is typically required. Critical thinking, problem-solving, and clear communication are crucial soft skills for interpreting data and collaborating with multidisciplinary teams. These skills ensure accurate data-driven decisions, efficient process improvements, and effective solutions to complex engineering challenges.

What is the difference between Statistical Engineering vs Data Scientist?

AspectStatistical EngineeringData Scientist
Required credentialsStatistics, Data Analysis, EngineeringStatistics, Computer Science, Data Analysis
Work environmentManufacturing, R&D, Engineering teamsBusiness, Tech, Research sectors
Employer usageOptimizing processes, designing experimentsBuilding models, insights, predictive analytics

Statistical Engineering focuses on applying statistical methods to improve engineering processes and product development, often within manufacturing or R&D settings. Data Scientists analyze large datasets to extract insights, build predictive models, and support business decisions. While both roles require strong statistical skills, Statistical Engineering emphasizes process optimization and experimental design, whereas Data Scientists focus on data-driven insights across diverse industries.

How does a Statistical Engineer typically collaborate with cross-functional teams to implement data-driven solutions?

Statistical Engineers frequently work alongside data scientists, software engineers, and business analysts to design and implement robust data-driven solutions. They are responsible for translating complex statistical models into actionable insights and ensuring that these models are integrated effectively within existing systems. Collaboration often involves regular meetings to align on project goals, sharing progress updates, and troubleshooting technical challenges together. This interdisciplinary teamwork is essential for ensuring that statistical methodologies are not only theoretically sound but also practically applicable to real-world business problems.

What is statistical engineering?

Statistical engineering is an interdisciplinary field that focuses on the integration and application of statistical methods and principles to solve complex, large-scale problems in science, business, and engineering. It involves designing data collection processes, analyzing and interpreting data, and implementing statistical solutions within larger systems. Statistical engineers often work on projects that require collaboration with other engineering disciplines, using statistics as a foundational tool to drive decision-making and innovation.
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$74K/yr

Other

Posted 11 days ago


Job description

See duties from the agency on available duty locations.
OIG is organized into six operational units: the Immediate Office of the Inspector General, Office of the Counselor, Office of Audits and Evaluations, Office of Healthcare Inspections, Office of Investigations, and Office of Management and Administration. In addition to the Washington, DC, headquarters, OIG has offices located in more than 60 locations throughout the country.Qualifications:

You must meet the following requirements within 30 days of the closing date of this announcement

To be qualified for this position at the GS-11 level, you must have at least one year of specialized experience equivalent to the GS-09 level that has equipped the applicant with the particular knowledge, skills, and abilities to perform successfully the duties of the position. Specialized experience is defined as:
- Assisting in researching and compiling data for inspection, audit and investigation activities; AND
- Supporting data processing and analysis using analytic platforms and software; AND
- Contributing to the development of data briefing, dashboards, presentations based on data analysis, etc. OR
- Ph.D. or equivalent doctoral degree OR
-3 full years of progressively higher level graduate education leading to a Ph.D. or equivalent doctoral degree OR
-LL.M., if related OR
-A combination of experience and education. To combine education and experience, the total percentage of experience at the required grade level compared to the requirement, as well as the percentage of completed education compared to the requirement, must equal at least 100 percent. Only graduate level education in excess of the first 36 semester hours (54 quarter hours) may be used in meeting this requirement.

In addition to the above requirements, you must meet the following time-in-grade requirement, if applicable:
For the GS-11, you must have been at the GS-9 level for 52 weeks.
To be found well-qualified, and in addition to meeting specialized experience, the applicant must have documented the following experience: Having a solid and comprehensive understanding of the position. Can perform the required tasks efficiently and is proficient in applying the knowledge, skills, and abilities of the job.
If you are a displaced or surplus Federal employee (eligible for the Career Transition Assistance Plan(CTAP)/Interagency Career Transition Assistance Plan (ICTAP)) you must be rated as "well qualified" to receive special selection priority.
Time After Competitive Appointment: Candidates who are current Federal employees serving on a nontemporary competitive appointment must have served at least three months in that appointment.

Education:You must meet the minimum basic education and/or work experience requirements for Statistician positions in the Federal government. These basic requirements include:
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
B. Combination of education and experience -- Courses as shown in A 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.
The education generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of EducationEmployment Type: OTHER