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Statistical Engineer Jobs in Florida (NOW HIRING)

U.S. Department of Defense (DOD)

$63K/yr

... and statistical sciences in order to design, test or upgrade software. Experience in administrative aspects of task engineering and management, e.g., procurement policies, preparation of work ...

US Department of the Air Force

$63K/yr

... and statistical sciences in order to design, test or upgrade software. Experience in administrative aspects of task engineering and management, e.g., procurement policies, preparation of work ...

U.S. Department of Defense (DOD)

$63K/yr

... and statistical sciences in order to design, test or upgrade software. Experience in administrative aspects of task engineering and management, e.g., procurement policies, preparation of work ...

US Department of the Air Force

$63K/yr

... and statistical sciences in order to design, test or upgrade software. Experience in administrative aspects of task engineering and management, e.g., procurement policies, preparation of work ...

AllSTEM Connections

Lead Engineer

Orlando, FL · On-site

$58K - $93K/yr

Utilize unique analytical techniques-including probability and statistics, process flow analysis ... Own the process of engineering, implementing, and institutionalizing systemic changes that improve ...

Lockheed Martin

Reliability Engineer Staff

Orlando, FL · On-site

$95K - $120K/yr

As the Reliability Engineer you will be responsible for driving reliability growth across our ... Recommend statistical process control methods and test techniques to achieve target reliability ...

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All JobsStatistical Engineer JobsStatistical Engineer Jobs in Florida

Statistical Engineer information

See Florida salary details

$24.7K

$70.3K

$108.7K

How much do statistical engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for statistical engineer in Florida is $70,268.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,900.00 and $81,100.00 per year, depending on experience, location, and employer.

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 skills in statistical analysis, mathematics, and data interpretation, usually backed by a degree in statistics, engineering, or a related field. Familiarity with statistical software (such as R, SAS, or Python), data visualization tools, and knowledge of quality control systems are typically required. Critical thinking, problem-solving, and effective communication are essential soft skills for translating data insights into actionable solutions. These skills ensure accurate data-driven decision-making and process optimization, which are vital for organizational success.

What are Statistical Engineers?

Statistical Engineers are professionals who apply statistical methods and techniques to solve engineering and production-related problems. They analyze data, design experiments, and develop models to optimize processes, improve product quality, and support decision-making in various industries. Their work often involves collaborating with engineers, scientists, and business teams to interpret data and implement solutions that enhance efficiency and reliability.

What is the salary of a Statistical Engineer?

The average salary of a Statistical Engineer typically ranges from $70,000 to $120,000 annually, depending on experience, education, and location. Professionals in this role often work with statistical software and data analysis tools, and advanced certifications can influence earning potential.

What is the difference between Statistical Engineer vs Data Scientist?

AspectStatistical EngineerData Scientist
Required CredentialsBachelor's or Master's in Statistics, Mathematics, or related field; often some programming skillsBachelor's or Master's in Data Science, Statistics, or related; strong programming and analytical skills
Work EnvironmentFocus on developing and optimizing statistical models, often in engineering or manufacturing settingsAnalyze large datasets, build predictive models, and communicate insights across various industries
Employer & Industry UsageUsed in manufacturing, engineering, and technology sectors for process improvementCommon in tech, finance, healthcare, and marketing for data analysis and modeling

While both roles require strong statistical knowledge and programming skills, Statistical Engineers primarily focus on developing and implementing statistical models within engineering contexts. Data Scientists tend to work more broadly on analyzing data, building predictive models, and deriving insights across diverse industries.

What does a Statistical Engineer do?

A Statistical Engineer designs and applies statistical models and data analysis techniques to solve complex problems, often working with large datasets and programming tools like R or Python. They develop algorithms, validate data quality, and collaborate with teams to improve processes and decision-making based on quantitative insights.

Are statisticians highly paid?

Statistical engineers and statisticians are generally well-paid professions, with salaries often above the national average due to their specialized skills in data analysis, modeling, and programming. Compensation varies based on experience, education, industry, and location, with roles requiring proficiency in tools like R, Python, or SAS typically offering higher salaries.

How does a Statistical Engineer typically collaborate with cross-functional teams in a project-driven environment?

Statistical Engineers often work closely with professionals from diverse fields such as data science, software engineering, quality assurance, and business analytics. In a project-driven environment, they are responsible for designing experiments, analyzing large datasets, and interpreting results to inform decision-making. Collaboration usually involves participating in regular meetings, communicating complex statistical findings in an accessible way, and ensuring that analytical methods align with the team's objectives. This cross-functional teamwork not only enhances project outcomes but also helps Statistical Engineers develop broader professional skills and a deeper understanding of the organization's operations.

What engineers make $500,000?

Highly experienced engineers in specialized fields such as petroleum engineering, aerospace engineering, or software engineering with senior or executive roles can earn $500,000 or more annually. These positions often require advanced skills, certifications, and extensive industry experience, and may include bonuses or stock options.
What are popular job titles related to Statistical Engineer jobs in Florida? For Statistical Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Statistical Engineer jobs in Florida look for? The top searched job categories for Statistical Engineer jobs in Florida are:
Statistical Engineer jobs near you
Infographic showing various Statistical Engineer job openings in Florida as of July 2026, with employment types broken down into 90% Full Time, 6% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $70,268 per year, or $33.8 per hour.
Information Technology_USA - USA_Data Scientist

Information Technology_USA - USA_Data Scientist

Real Soft, Inc.

Jacksonville, FL • On-site

Contractor

Re-posted 2 days ago

Job description

Local to Raleigh, NC Only!
Role Overview
We are seeking a highly experienced Senior Statistical Programmer / Clinical Data Architect with 15+ years of expertise in clinical data programming, CDISC standards, and cloud-based analytics platforms. The ideal candidate will lead end-to-end clinical data workflows, regulatory submissions, and modern data platform transformations in GxP-regulated environments.
This role requires strong domain expertise in SDTM, ADaM, regulatory submissions, and SAS/Python/R programming, combined with experience in cloud platforms (AWS/Azure) and clinical data modernization initiatives.
Key Responsibilities
Clinical Data Programming & Regulatory Submissions
• Design, develop, and validate SDTM and ADaM datasets in compliance with CDISC standards
• Lead generation of define.xml, aCRF/eCRF annotations, and submission-ready deliverables
• Develop and optimize automated submission pipelines for FDA and global regulatory authorities
• Ensure compliance with GxP, 21 CFR Part 11, HIPAA, and ICH E6 guidelines
Data Engineering & Automation
• Architect and implement end-to-end clinical data pipelines using SAS, Python, and R
• Develop reusable SAS macro libraries and automation frameworks
• Build scalable data pipelines including modern formats (JSON/XPT alternatives)
• Drive migration from legacy systems to modern data architectures
Cloud & Platform Engineering
• Lead implementation and optimization of SAS Viya platforms on AWS/Azure
• Manage cloud infrastructure components (EKS, EC2, EFS, FSx, Databricks, etc.)
• Implement FinOps practices for cost governance and optimization
• Evaluate and onboard next-gen analytics platforms (e.g., Databricks)
Leadership & Stakeholder Management
• Lead cross-functional teams across US, UK, and offshore locations
• Collaborate with clinical, statistical, regulatory, and IT stakeholders
• Drive Agile delivery and sprint planning for data and platform initiatives
• Manage vendor relationships, tool selection, and licensing strategies
Compliance & Governance
• Ensure adherence to regulatory and audit requirements (FDA, OCC, SOX, Basel III as applicable)
• Maintain audit-ready documentation and validation processes
• Implement data governance, traceability, and reproducibility standards
Required Qualifications
• Bachelor's or Master's degree in Computer Science, Statistics, Life Sciences, or related field
• 15+ years of experience in statistical programming and clinical data management
• Strong expertise in:
o SAS (Base, Macro, SQL, ODS, STAT, Graph)
o CDISC standards (SDTM, ADaM, define.xml)
o Regulatory submissions (FDA, global agencies)
• Hands-on experience with:
o Python (Pandas) and/or R (admiral, Shiny)
o Cloud platforms (AWS/Azure)
• Strong understanding of GxP and clinical compliance frameworks
Preferred Qualifications
• Experience with SAS Viya architecture and administration
• Familiarity with Databricks, DBT, or modern data engineering tools
• Knowledge of CI/CD tools (Jenkins, Git)
• Experience in financial/regulatory environments (Basel III, CCAR, OCC) is a plus
• AWS or cloud certifications
Key Skills
• Clinical Data Standards: SDTM, ADaM, CDISC
• Programming: SAS, Python, R, SQL
• Cloud: AWS, Azure
• Tools: Pinnacle 21, Git, Jenkins, Power BI, Grafana
• Methodologies: Agile, DevOps, Data Governance
Role Descriptions: Key ResponsibilitiesClinical Data Programming & Regulatory SubmissionsDesign| develop| and validate SDTM and ADaM datasets in compliance with CDISC standardsLead generation of define.xml| aCRF/eCRF annotations| and submission-ready deliverablesDevelop and optimize automated submission pipelines for FDA and global regulatory authoritiesEnsure compliance with GxP| 21 CFR Part 11| HIPAA| and ICH E6 guidelinesData Engineering & AutomationArchitect and implement end-to-end clinical data pipelines using SAS| Python| and RDevelop reusable SAS macro libraries and automation frameworksBuild scalable data pipelines including modern formats (JSON/XPT alternatives)Drive migration from legacy systems to modern data architecturesCloud & Platform EngineeringLead implementation and optimization of SAS Viya platforms on AWS/AzureManage cloud infrastructure components (EKS| EC2| EFS| FSx| Databricks| etc.)Implement FinOps practices for cost governance and optimizationEvaluate and onboard next-gen analytics platforms (e.g.| Databricks)Leadership & Stakeholder ManagementLead cross-functional teams across US| UK| and offshore locationsCollaborate with clinical| statistical| regulatory| and IT stakeholdersDrive Agile delivery and sprint planning for data and platform initiativesManage vendor relationships| tool selection| and licensing strategiesCompliance & GovernanceEnsure adherence to regulatory and audit requirements (FDA| OCC| SOX| Basel III as applicable)Maintain audit-ready documentation and validation processesImplement data governance| traceability| and reproducibility standardsRequired QualificationsBachelors or Masters degree in Computer Science| Statistics| Life Sciences| or related field15+ years of experience in statistical programming and clinical data managementStrong expertise in: oSAS (Base| Macro| SQL| ODS| STAT| Graph)oCDISC standards (SDTM| ADaM| define.xml)oRegulatory submissions (FDA| global agencies)Hands-on experience with: oPython (Pandas) and/or R (admiral| Shiny)oCloud platforms (AWS/Azure)Strong understanding of GxP and clinical compliance frameworksPreferred QualificationsExperience with SAS Viya architecture and administrationFamiliarity with Databricks| DBT| or modern data engineering toolsKnowledge of CI/CD tools (Jenkins| Git)Experience in financial/regulatory environments (Basel III| CCAR| OCC) is a plusAWS or cloud certificationsKey SkillsClinical Data Standards: SDTM| ADaM| CDISCProgramming: SAS| Python| R| SQLCloud: AWS| AzureTools: Pinnacle 21| Git| Jenkins| Power BI| GrafanaMethodologies: Agile| DevOps| Data Governance
Essential Skills: Key ResponsibilitiesClinical Data Programming & Regulatory SubmissionsDesign| develop| and validate SDTM and ADaM datasets in compliance with CDISC standardsLead generation of define.xml| aCRF/eCRF annotations| and submission-ready deliverablesDevelop and optimize automated submission pipelines for FDA and global regulatory authoritiesEnsure compliance with GxP| 21 CFR Part 11| HIPAA| and ICH E6 guidelinesData Engineering & AutomationArchitect and implement end-to-end clinical data pipelines using SAS| Python| and RDevelop reusable SAS macro libraries and automation frameworksBuild scalable data pipelines including modern formats (JSON/XPT alternatives)Drive migration from legacy systems to modern data architecturesCloud & Platform EngineeringLead implementation and optimization of SAS Viya platforms on AWS/AzureManage cloud infrastructure components (EKS| EC2| EFS| FSx| Databricks| etc.)Implement FinOps practices for cost governance and optimizationEvaluate and onboard next-gen analytics platforms (e.g.| Databricks)Leadership & Stakeholder ManagementLead cross-functional teams across US| UK| and offshore locationsCollaborate with clinical| statistical| regulatory| and IT stakeholdersDrive Agile delivery and sprint planning for data and pla, Project Code :

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