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Internship Next Gen Stats Jobs (NOW HIRING)

Implement Next-Gen Tech: Apply state-of-the-art neural rendering and view-synthesis techniques ... Pursuing MS or PhD in CS, EE, mathematics, statistics or related field * Deep understanding of ...

Implement Next-Gen Tech: Apply state-of-the-art neural rendering and view-synthesis techniques ... Pursuing MS or PhD in CS, EE, mathematics, statistics or related field * Deep understanding of ...

Join us in developing solutions for next-gen touch technologies! The team features a collaborative ... statistical analysis tools such as Tableau, SpotFire, JMP, Python or Matlab or similarExcellent ...

Join us in developing solutions for next-gen touch technologies! The team features a collaborative ... statistical analysis tools such as Tableau, SpotFire, JMP, Python or Matlab or similarExcellent ...

Establish, monitor, and maintain statistical process control (SPC) limits for key products and processes within the melt and remelt departments. * Provide technical support in resolving process ...

Reliability Engineer (Starlink/Akoustis)

Bastrop, TX · On-site

$101K - $128K/yr

Develop, validate, and implement production processes for existing and next-gen hardware with ... implement statistical process controls * Conduct regular build quality reviews to ensure that ...

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Internship Next Gen Stats information

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How much do internship next gen stats jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for internship next gen stats in the United States is $15.54, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $17.55 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Next Gen Stats, and why are they important?

To thrive in a Next Gen Stats Internship, you need a solid foundation in data analysis, statistics, and a relevant field of study such as computer science or sports analytics. Familiarity with tools like Python, R, SQL, and data visualization platforms, as well as experience with sports data APIs, is typically expected. Strong problem-solving skills, attention to detail, and effective communication help you interpret complex data and present insights clearly. These skills are important for extracting actionable information from large datasets and supporting data-driven decision-making in sports organizations.

What types of projects and day-to-day tasks can I expect during an Internship with the Next Gen Stats team?

As an intern with the Next Gen Stats team, you can expect to work on a variety of data-centric projects, such as analyzing player tracking data, assisting with research on football analytics, and helping develop new statistical models or visualization tools. Your daily tasks may include cleaning and processing large datasets, collaborating with data scientists and engineers, and presenting analytical findings to team members. This role offers hands-on experience with innovative sports technology and provides opportunities to contribute to impactful projects that influence game broadcasts and fan engagement.

What are Internship Next Gen Stats?

Internship Next Gen Stats refers to internship positions that focus on the analysis, development, or support of advanced statistical data, often used in sports or technology industries. These internships typically involve working with large datasets, utilizing data analytics tools, and helping organizations gain deeper insights from modern data collection methods. Interns may assist with research, data visualization, and the implementation of new statistical models. The goal is to help organizations leverage next-generation statistics for improved decision-making and performance analysis.

What is the difference between Internship Next Gen Stats vs Sports Data Intern?

AspectInternship Next Gen StatsSports Data Intern
Required CredentialsEnrolled in sports analytics, data science, or related programsSimilar; often pursuing sports management, analytics, or related fields
Work EnvironmentSports analytics companies, professional teams, or media outletsSports organizations, media, or analytics firms
Industry UsageFocuses on advanced player tracking and Next Gen Stats dataGeneral sports data collection and analysis
Common Search/ComparisonInternship Next Gen Stats vs Sports Data Intern

The Internship Next Gen Stats role specializes in advanced sports tracking data, often requiring knowledge of analytics and data science. In contrast, a Sports Data Intern may handle broader sports data collection and analysis. Both roles are valuable entry points into sports analytics, but Next Gen Stats internships focus more on cutting-edge tracking technology and detailed player metrics.

More about Internship Next Gen Stats jobs
What cities are hiring for Internship Next Gen Stats jobs? Cities with the most Internship Next Gen Stats job openings:
What are the most commonly searched types of Next Gen Stats jobs? The most popular types of Next Gen Stats jobs are:
What states have the most Internship Next Gen Stats jobs? States with the most job openings for Internship Next Gen Stats jobs include:
Infographic showing various Internship Next Gen Stats job openings in the United States as of May 2026, with employment types broken down into 7% As Needed, 7% Full Time, and 86% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $32,333 per year, or $15.5 per hour.
Information Technology_USA - USA_Data Scientist

Information Technology_USA - USA_Data Scientist

Real Soft, Inc.

Jacksonville, FL • On-site

Contractor

Posted 27 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 :