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Statistical Engineering Jobs in Georgia (NOW HIRING)

Kemper

Data Scientist

Alpharetta, GA · On-site +1

Graduate degree inMathematics,Statistics,Engineering, or other STEM field with2-4 yearsofexperience working in a data science/analyticsenvironment. * PhD inMathematics,Statistics,Engineering, or ...

Munich Re

Data Scientist

Atlanta, GA · On-site +1

Proficiency in statistical programming languages such as R, Python, SAS, or similar, alongside general programming and SQL knowledge. * Demonstrated experience building and deploying statistical and ...

Guidehouse

Biostatistician Lead

Atlanta, GA

Experience in statistical programming using SAS and at least one additional statistical language such as R or Python. * Experience developing and reviewing Statistical Analysis Plans (SAPs ...

The Marzetti Company

Quality Engineer II

College Park, GA · On-site

$85 - $110/hr

... engineering support to manufacturing operations by applying statistical methods, risk analysis, quality engineering principles, and continuous improvement tools to improve product quality and ...

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All JobsStatistical Engineering JobsStatistical Engineering Jobs in Georgia

Statistical Engineering information

See Georgia salary details

$51.6K

$60.5K

$67.6K

How much do statistical engineering jobs pay per year?

As of Aug 21, 2026, the average yearly pay for statistical engineering in Georgia is $60,550.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,200.00 and $64,600.00 per year, depending on experience, location, and employer.

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 Georgia?

For Statistical Engineering jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Statistical Engineering jobs in Georgia look for?

The top searched job categories for Statistical Engineering jobs in Georgia are:

What cities in Georgia are hiring for Statistical Engineering jobs?

Cities in Georgia with the most Statistical Engineering job openings:

Statistical Engineering jobs near you
Infographic showing various Statistical Engineering job openings in Georgia as of August 2026, with employment types broken down into 84% Full Time, 6% Part Time, 7% Contract, and 3% Nights. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $60,550 per year, or $29.1 per hour.

Data Reporting and Analytics Consultant II

Kaiser Permanente

Atlanta, GA • On-site

$85 - $120/hr

Other

Posted 6 days ago

Job description

Overview:

The Data Reporting and Analytics Consultant II is an individual contributor who will support Kaiser Permanente-s Medicaid line of business and serve as the subject matter expert for membership performance. This role analyzes and forecasts membership trends, translating complex market dynamics, competitive positioning, and regulatory impacts into clear, actionable insight.

Job Summary:

This individual contributor is primarily responsible for assisting senior employees in supporting data-informed decisions, assisting with data and information gathering for targeted variables in an established systematic fashion, and supporting data preparation for analytic efforts. This position assists with the execution of creative data analytic approaches leading to actionable outcomes, assists with the development, implementation, and automation of business and reporting solutions, and assists with data analysis interpretation.

Essential Responsibilities:
  • Pursues self-development and effective relationships with others by sharing resources, information, and knowledge with coworkers and customers; listening, responding to, and seeking performance feedback; acknowledging strengths and weaknesses; assessing and responding to the needs of others; and adapting to and learning from change, difficulties, and feedback.
  • Completes work assignments by applying up-to-date knowledge in subject area to meet deadlines; following procedures and policies and applying data, and resources to support projects or initiatives; collaborating with others, often cross-functionally, to solve business problems; supporting the completion of priorities, deadlines, and expectations; communicating progress and information; identifying and recommending ways to address improvement opportunities when possible; and escalating issues or risks as appropriate.
  • Assists with data analysis interpretation by organizing and editing reports and presentations telling a compelling story to stakeholders to enable and influence decision making.
  • Supports data-informed decisions under the guidance of more senior employees by working with clients to identify and clarify key business needs; assisting in the development of outcomes and process measures; translating business requirements; informing data/information needs and data collection methods; measuring the impact of business decisions on clients, customers, and/or members; working with clients and staff to identify opportunities and methods to improve efficiencies with analysis; supporting end-users; and documenting processes and deliverables.
  • Assists with data and information gathering for targeted variables in an established systematic fashion by cleaning and organizing data; querying, merging, and extracting data across sources; completing routine data refresh and update; and providing user support and documentation.
  • Supports data preparation for analytic efforts under the guidance of more senior employees by cleaning data to ensure quality and accuracy based on provided guidelines; and consolidating data.
  • Assists with the execution of creative data analytic approaches leading to actionable outcomes by organizing metrics to be analyzed and calculating algorithms and conducting basic analyses under the guidance of more senior employees, including descriptive statistics.
  • Assists with the development, implementation, and automation of business and reporting solutions by creating summary statistics; organizing data reports, visualizations, and/or interactive Business Intelligence (BI) reports; identifying opportunities to improve exiting reporting solutions; and preparing documentation as appropriate.
Knowledge, Skills and Abilities: (Core)
  • Ambiguity/Uncertainty Management
  • Attention to Detail
  • Business Knowledge
  • Communication
  • Critical Thinking
  • Cross-Group Collaboration
  • Decision Making
  • Dependability
  • Diversity, Equity, and Inclusion Support
  • Drives Results
  • Facilitation Skills
  • Health Care Industry
  • Influencing Others
  • Integrity
  • Learning Agility
  • Organizational Savvy
  • Problem Solving
  • Short- and Long-term Learning & Recall
  • Teamwork
  • Topic-Specific Communication
Knowledge, Skills and Abilities: (Functional)
  • Data Mining
  • Data Visualization Tools
  • Statistical Programming Language
  • Written Communication
Minimum Qualifications:
  • Bachelors degree in Mathematics, Statistics, Engineering, Social/Physical/Life Science, Business, or related field OR Minimum two (2) years experience in data analytics or a directly related field.
Preferred Qualifications:
  • One (1) year experience working with Access.
  • One (1) year data simulation experience.
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