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Statistical Engineering Jobs in Virginia Beach, VA

Rivet

Engineering / Architecture Analyst

Norfolk, VA · On-site

$75K - $86K/yr

Use engineering and statistical software to perform analyses; assist in developing tools to perform analyses where none exist * Conduct and present the results of engineering studies * Perform ...

Rivet

Engineering / Architecture Analyst

Norfolk, VA

$75K - $86K/yr

Use engineering and statistical software to perform analyses; assist in developing tools to perform analyses where none exist * Conduct and present the results of engineering studies * Perform ...

Rivet

Engineering / Architecture Analyst

Norfolk, VA · On-site

$75K - $86K/yr

Use engineering and statistical software to perform analyses; assist in developing tools to perform analyses where none exist * Conduct and present the results of engineering studies * Perform ...

Busch Group

Industrial Engineer

Chesapeake, VA · On-site

$70 - $90/hr

Conduct statistical data analysis to identify trends, patterns, and opportunities for process improvement utilizing key data analysis and visualization tools such as Excel, Python, R Programming ...

N-C

Industrial Engineer

Chesapeake, VA · On-site

$92K - $114K/yr

Conduct statistical data analysis to identify trends, patterns, and opportunities for process improvement utilizing key data analysis and visualization tools such as Excel, Python, R Programming ...

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Statistical Engineering information

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.

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 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.

What do statistical engineers do?

Statistical engineers develop and implement statistical models and methods to analyze complex data, often focusing on process improvement and quality control. They use tools like statistical software and programming languages such as R or Python and collaborate with data scientists and engineers to optimize systems and decision-making processes.

What are popular job titles related to Statistical Engineering jobs in Virginia Beach, VA?

For Statistical Engineering jobs in Virginia Beach, VA, the most frequently searched job titles are:

What job categories do people searching Statistical Engineering jobs in Virginia Beach, VA look for?

The top searched job categories for Statistical Engineering jobs in Virginia Beach, VA are:

What cities near Virginia Beach, VA are hiring for Statistical Engineering jobs?

Cities near Virginia Beach, VA with the most Statistical Engineering job openings:

Statistical Engineering jobs near you

SAS-to-R/Python Migration Lead with Security Clearance

Hampton, VA • On-site

Blu Omega LLC
IT Services • 51 - 200 employees
Learn more about Blu Omega LLCexternal

$92K - $101K/yr

Other

Posted 4 days ago

Job description

SAS-to-R/Python Migration Lead Remote Blu Omega is seeking a SAS-to-R/Python Migration Lead to support a federal program focused on HIV surveillance, data modernization, and public health analytics. This role operates within a remote environment and is responsible for leading analytics modernization efforts across complex public health data environments. The position requires experience supporting data modernization, statistical programming, and stakeholder engagement to improve public health outcomes. Program Overview Supports CDC efforts to modernize HIV data collection and analysis, examining program effectiveness, HIV prevalence, resistance mutations, and outbreak clusters. Key Details Location: Remote Clearance: Public Trust Eligible Responsibilities * Lead analytics modernization initiatives supporting surveillance, research, and program evaluation. * Develop strategies, roadmaps, coding standards, and governance frameworks for analytic transformation. * Assess legacy SAS environments, workflows, and reporting pipelines to identify modernization opportunities. * Lead migration of SAS workflows to R and Python, ensuring analytic intent and output consistency. * Design validation frameworks to confirm equivalence between legacy and modernized workflows. * Establish and maintain code review standards, automated validation, and reproducibility controls. * Collaborate with biostatisticians and epidemiologists to validate migrated outputs. * Develop reusable libraries, templates, and frameworks to increase consistency and efficiency. * Support implementation of cloud-based analytics environments and scalable data science platforms. * Establish enterprise standards for reusable analytics and technical documentation. * Mentor technical teams in R, Python, Git, testing methodologies, and modern development practices. * Develop technical designs, migration inventories, validation reports, and training materials. * Support proposal efforts and thought leadership activities related to analytics modernization. Required Qualifications * U.S. Citizen or Permanent Resident with ability to obtain and maintain a Public Trust clearance. * Bachelors degree in Computer Science, Data Science, Statistics, Biostatistics, Informatics, Engineering, or related field; Master's preferred. * 8+ years supporting analytics modernization, statistical programming, or data science. * Experience leading SAS to R/Python migration initiatives. * Expertise in SAS programming, including macros, PROC SQL, data step, and reporting workflows. * Proficiency in R and Python, including development of reusable packages and automated workflows. * Experience designing validation frameworks, regression testing, and quality control processes. * Strong collaboration skills with biostatisticians, epidemiologists, and data scientists. * Experience with Git, GitHub, Azure DevOps, CI/CD pipelines, and software development lifecycle. * Ability to develop and maintain technical documentation, migration plans, and validation reports. Preferred Qualifications * Master's degree in Data Science, Computer Science, Statistics, or related discipline. * Experience supporting analytic workflows in healthcare, public health, or government environments. * Strong problem-solving and stakeholder engagement skills. * Experience leading technical workstreams and mentoring multidisciplinary teams. * Knowledge of modern analytics platforms such as Databricks, Snowflake, Azure, or AWS. * Experience with CI/CD, DataOps, MLOps, containerization, and automated deployment frameworks. * Experience developing enterprise analytics frameworks and supporting large-scale public health systems. * Prior work with state public health agencies or federal health organizations. Salary Range $92,000.00 - $101,000.00 #CJ #LI-Remote

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